XRP vs Stellar XLM

XRP vs Stellar (XLM): Which is Better for Cross-Border Payments?

December 3, 2018 By Danielys Bluetower

Original Source Article

Here are excerpts from two current articles on the website elevenews.com that helped greatly to explain the relationship between several cryptocurrencies being developed for digital currency transactions.

The on-going discussion is about which one will be the best to use for cross-border payment solutions.

Both XRP and Stellar Lumens (XLM) are distributed ledger technology (DLT)-based platforms that aim to provide cross-border payments solutions between large banks and financial firms. However, Stellar’s products have also been developed for the individual consumer.

Notably, the Stellar payment network is a fork of the Ripple protocol and was founded by Jed McCaleb in 2014. McCaleb is also the co-founder of the Ripple protocol. When the Stellar project was proposed, a non-profit Development Foundation was launched as well – in order to support the ongoing development of the Stellar platform.

Stellar Backed By Stripe

One key difference between XRP and Stellar is that the latter was created by a non-profit organization. Due partly to the lower overhead costs of operating as a non-profit entity, the transaction fees on Stellar’s network are quite low. Early stage investors in the Stellar project include San Francisco-based Stripe, an internet-based payment processing service.

Similar to how the XRP cryptocurrency (developed by Ripple Labs) is used to facilitate transfers between two parties who may use different fiat currencies, the Stellar network also allows users to send and receive payments to/from bank accounts that support different currencies – without having to pay high currency conversion fees.

Transactions Only Cost Fractions Of A Cent

For example, the Stellar network can be used to send a payment in British pounds (GBP) to an account that accepts USD. The sender of the payment on the platform only has to pay a 0.00001 XLM network usage fee – which is only a fraction of a cent.

San Francisco-based Ripple Labs has also developed products which are quite similar to those offered by Stellar. XRP is a cryptocurrency that was developed by Ripple Labs and its transactions are conducted on the XRP ledger, at incredibly small costs. In order to transact on the XRP ledger, however, an address must hold at least 20 XRP.

As explained on Ripple’s official website, users must hold a minimum of 20 XRP so that “the shared [XRP] global ledger [does not] grow excessively large as [a] result of spam or malicious usage.”

xCurrent

As most XRP community members would know, not all of Ripple’s products use XRP as the base currency. xCurrent, which does not use the token, is an enterprise-level software product that utilizes the Interledger Protocol (ILP) to “instantly” process international payments – as it allows for “inter-operability” between virtual and fiat currencies.

The Interledger Protocol was created by Ripple Labs, but its ongoing management and development is now handled by the World Wide Web Consortium (W3C) group. The W3C is an international body that creates open standards to support further growth of the internet.

MoneyGram Tests xRapid, xCurrent Supports Real-Time Messaging

Notably, xCurrent supports real-time messaging between banks (similar to SWIFT) – which is useful because static messages may have typos or might not include important information. This often leads to transactions being delayed.

Another popular product developed by Ripple Labs, xRapid, was also launched recently. If XRP is used to send payments using xCurrent, then Ripple refers to these types of transactions as xRapid. Prior to going live (production), xRapid was tested by leading money transfer services such as Western Union and MoneyGram.

One of the main benefits of using xRapid, according to Ripple, is that it provides liquidity through XRP – which allows money to be transferred cheaply and quickly.

Public Vs Private DLT Networks

Although Ripple, the company, claims to have partnered with around 150 different financial institutions who are either currently testing its products or are even using them in a production environment, the American fintech’s critics say that transactions on RippleNet are not transparent. That’s because it’s a private DLT-based payment network.

However, digital currency transactions on the Stellar network can be verified and seen by anyone – which is something that generally holds true for most public blockchains. Another thing which Stellar’s community focuses more on, compared to Ripple, is serving the underbanked – meaning helping to provide financial services to people who do not have access to modern banking services.

The Light from Your Phone Breaks Your Internal Clock

This is how the light from your phone breaks your internal clock

It’s not just sleep: circadian rhythms influence your metabolism, circulation and psychology, too

Original source article

On December 30th, 1882, at twenty minutes past eight, the first electric streetlights were turned on in Los Angeles. The few lamps, placed in the center of town, cast a gentle glow that was compared to “the full moon on snow”. About a hundred years later, when an earthquake knocked out power to the city, a nearby observatory fielded calls from confused Angelenos asking about a strange cloud now visible in the night sky. The observatory told them not to worry–they were just, for the first time, able to see the Milky Way.

Nope, no Milky Way hereMUHD ASYRAAF

Now, over a century after we lit the first electric streetlights, much of the world lives under light-polluted skies. Over 80%of the globe is covered in light pollution and one third of humanity is unable to see the Milky Way. While our ancestors had no choice but to live in sync with the natural cycle of light and dark, thanks to artificial light, modern life is a bit more chaotic. Many of us are active at night, sedentary during the day, and lie in bed bathed in the comforting, blue-hued glow of our smartphones.

While many of us consider all that to be relatively harmless, there’s a growing body of research showing that the consequences of messing up the internal clocks of nearly all of humanity might be more serious than we think. Irregular circadian rhythms have been linked to nearly every health problem under the sun: from heart attacks to cancer and diabetes to depression. So, should we turn off all the streetlights and throw our smartphones into the sea? And how could something as simple as light be so harmful, anyway?

The problem with light at night has to do with how the mammalian internal clock works. If you took a person and plunged them into total darkness, they would keep going to sleep and waking up at about the same time each day. But, the internal clock is imprecise. Over time, that person would drift out of sync with the objective timing of night and day. The major signal that sets the internal clock to the correct time is light.

More specifically, there are certain rare types of cells within the eye that sense light but, unlike rods and cones, have nothing to do with sight. Instead, they transfer the message that it is day directly to the brain’s central clock. These cells respond most strongly to blue light, which is why some computer screensnow shift to the warmer, red side of the color spectrum after dark. And they don’t need to be exposed to light for a long time to react: a brief pulse of light at night is enough to reset the brain’s central clock.

Red light, blue light, some sleep, no sleepDANIEL JOSEF

Once the central clock is set, it coordinates the timing of other peripheral clocks throughout the body. Although most people know that circadian rhythms control sleep, sleep is just one of many processes that depend on the clock.

Another one of those processes is metabolism. Insulin levels rise and fall according to the time of day, except in diabetics, who have irregular cycles of insulin secretion. And levels of the hormone leptin, which makes people feel full, and ghrelin, which makes people feel hungry, are also controlled by the clock.

We’ve known for a long time that shift workers, especially those who work the graveyard shift, have a higher incidence of obesity, diabetes, and other metabolic issues. But it can be difficult to pin down how much of that is due specifically to irregular circadian rhythms. To figure out whether the connection is real, scientists looked at mice with mutations in a gene called Clock.

As you might be able to guess from the name, the gene Clock codes for a protein that’s an important part of the brain’s central clock. So, by disrupting that gene alone, researchers were able to pinpoint what happens when you break the internal clock, apart from all other factors. They found that Clock mutant mice ate at irregular hours, were obese, and had a host of metabolic abnormalities, including high blood sugar, high cholesterol, and low insulin.

What’s the connection between the internal clock and metabolism? One clue comes from a study where mice were subjected to conditions mimicking chronic jet lag – that is, the researchers shifted the time when the lights were on backwards or forwards by eight hours every week. The jet lagged mice gained weight and became resistant to leptin, which is one of the hallmarks of obesity in humans because leptin inhibits the feeling of hunger. And in humans, just a few nights of restricted sleep decreases the amount of leptin while increasing the amount of its partner, ghrelin, which promotes hunger. So it may be that a broken internal clock contributes to metabolic problems because it disrupts the hormones that tell us when to eat.

Humans spent hundreds of thousands of years living in time with clear day and night, so circadian rhythms control more than you’d think. Not only do sleep and metabolism depend on the internal clock, but so do blood pressure and heart rate, which contributes to the strange fact that heart attacks and strokes happen much more frequently in the morning. Circadian rhythms affect psychology, too. Shifting sleep-wake cycles earlier seems to make people feel happier, while the opposite contributes to depression. This is seen in studies of travelers who have to be hospitalized for psychiatric conditions after arriving at airports: they’re more likely to experience either depression or maniadepending on whether the time zone change shifted them forward or back. So the next time you’re tempted to check your phone in bed or pull an all-nighter, remember that when it comes to human health, it’s all in the timing.

5G Coming: Will It Kill Us All?

NEW 5G WIFI COMING AND IT WILL KILL US ALL. THIS IS SERIOUS! (And it shouts out a very attention-getting headline, too!)

First, there was 3G, then 4G and now we are heading into the era of 5G, while this is said to be an improvement it is also bringing with it harmful ultra-high microwave frequency radiation.

Are the health risks of implementing the new 5G technology really that alarming?

People who have raised their voices about the dangers that the technology will bring and who have talked about safety have been subjected to intimidation and harassment alongwith attempts to try to silence them.

Serious Health Risks Associated with 5G – Including Cancer

The FCC voted on July 14 to bring 5G to the US to make spectrum bands above 24 GHz available for the 5G technology, despite the fact that with the proliferation of technology for cellphones there are serious health risks.

It looks like the FCC has the attitude of going full speed ahead and not giving a thought to the torpedoes. June 20 saw the chairman of the FCC, Tom Wheeler, praising the rollout of 5G applications along with networks and he called them a game changer and went on to say that it would bring in tens of billions of dollars.

5G Uses Frequencies That Have Not Been Tested

The 5G network is going to use frequency bands that are higher and which had previously not been thought possible, frequencies of 24 to 100GHz, which have not been tested. Of course, the new and untested frequencies are going to need new antennas and these are designed to amplify signals. It means huge deployment of cells phone towers all overthe US.

The first to begin 5G trials in the US will be Verizon and ATT and these started in 2017, with the first deployment commercially to start in 2020. Wheeler said that all regions, including those in rural communities, will be saturated with 5G. This means that no part of the country is going to remain safe from the ultra-high frequency signals.

Reporter Silenced Over Worries About Health

At a press conference on July 14, Todd Shields, a reporter for Bloomberg News, had his press credentials taken from him by the FCC securityforce simply because he was speaking with safety advocates about radiation and he was concerned. He had confronted Wheeler during the conference and told him that his credentials had been taken and while Wheeler said that he could have them back, he did go on to tell Shields that everyone at the conference had to behave responsibly.

This meant that he had to follow orders otherwise he was out. Bear in mind that in the past the government has tested and then said that many things were safe and would not hurt the public.

These have included thalidomide, asbestos, lead paint and smoking, all of these have now been said to be otherwise and far from safe.

Study Revealed Wireless Radiation Can Cause Cancer

The National Toxicology Program conducted a government study to the cost of $25 million and it concluded that wireless radiation cancause cancer. 70% of the non-industry studies have revealed that wireless radiation is harmful, but with industry studies, this percentage is only 32%.

So far there is no getting away from the fact that the dangers are being ignored by the government. Even Verizon and T-Mobile annual financial reports have revealed that the phone companies acknowledge that they are subject to litigation in relation to alleged health effects or radio frequency transmitters and wireless phones.

They have warned that it may result in damages that are significant and they have admitted that wireless technology along with health effects that are adverse do actually exist, and this is said to include cancer being a threat.

Nokia is a defendant in a total of 19 different lawsuits that were filed in Washington D.C. which have alleged that radio emissions coming from cell phones have been the cause of brain tumors.

A Question For All Of Us

Should the health of people in the US and the rest of the world be risked solely to advance in mobile technology that ensures that people can get an even better cell phone signal wherever they are?

Teen Depression Signs Point To Smartphones

The number of teens who are depressed is soaring — and all signs point to smartphones

teen phone charging sad Time spent on social media was linked to mental health decline. Strelka Institute/Flickr

  • The number of American teens with depressed thoughts has been increasing since 2012.
  • Looking at the data, it’s possible to rule out some factors that might be causing it, like economic inequality and academic pressure.
  • Jean Twenge, author of “iGen,” believes all signs point to increased smartphone use as the likely cause.
  • Twenge says it’s not necessarily the screen time but the time that’s lost to smartphones that could be spent on more meaningful activities, like face-to-face interaction.

Around 2012, something started going wrong in the lives of teens.

In just the five years between 2010 and 2015, the number of U.S. teens who felt useless and joyless – classic symptoms of depression – surged 33 percent in large national surveys. Teen suicide attempts increased 23 percent. Even more troubling, the number of 13- to 18-year-olds who committed suicide jumped 31 percent.

In a new paper published in Clinical Psychological Science, my colleagues and I found that the increases in depression, suicide attempts and suicide appeared among teens from every background – more privileged and less privileged, across all races and ethnicities and in every region of the country.

All told, our analysis found that the generation of teens I call “iGen” – those born after 1995 – is much more likely to experience mental health issues than their millennial predecessors.

What happened so that so many more teens, in such a short period of time, would feel depressed, attempt suicide and commit suicide?

After scouring several large surveys of teens for clues, I found that all of the possibilities traced back to a major change in teens’ lives: the sudden ascendance of the smartphone.

Because the years between 2010 and 2015 were a period of steady economic growth and falling unemployment, it’s unlikely that economic malaise was a factor. Income inequality was (and still is) an issue, but it didn’t suddenly appear in the early 2010s: This gap between the rich and poor had been widening for decades.

We found that the time teens spent on homework barely budged between 2010 and 2015, effectively ruling out academic pressure as a cause.

However, according to the Pew Research Center, smartphone ownership crossed the 50 percent threshold in late 2012 – right when teen depression and suicide began to increase. By 2015, 73 percent of teens had access to a smartphone.

cell phone Teens spend much less time interacting with their friends in person. Nam Y. Huh/AP

Not only did smartphone use and depression increase in tandem, but time spent online was linked to mental health issues across two different data sets.

We found that teens who spent five or more hours a day online were 71 percent more likely than those who spent only one hour a day to have at least one suicide risk factor (depression, thinking about suicide, making a suicide plan or attempting suicide). Overall, suicide risk factors rose significantly after two or more hours a day of time online.

Of course, it’s possible that instead of time online causing depression, depression causes more time online. But three other studies show that is unlikely (at least, when viewed through social media use).

Two followed people over time, with both studies finding that spending more time on social media led to unhappiness, while unhappiness did not lead to more social media use. A third randomly assigned participants to give up Facebook for a week versus continuing their usual use. Those who avoided Facebook reported feeling less depressed at the end of the week.

The argument that depression might cause people to spend more time online doesn’t also explain why depression increased so suddenly after 2012.

Under that scenario, more teens became depressed for an unknown reason and then started buying smartphones, which doesn’t seem too logical.

Even if online time doesn’t directly harm mental health, it could still adversely affect it in indirect ways, especially if time online crowds out time for other activities.

For example, while conducting research for my book on iGen, I found that teens now spend much less time interacting with their friends in person.

Interacting with people face to face is one of the deepest wellsprings of human happiness; without it, our moods start to suffer and depression often follows. Feeling socially isolated is also one of the major risk factors for suicide.

We found that teens who spent more time than average online and less time than average with friends in person were the most likely to be depressed. Since 2012, that’s what has occurred en masse: Teens have spent less time on activities known to benefit mental health (in-person social interaction) and more time on activities that may harm it (time online).

Teens are also sleeping less, and teens who spend more time on their phones are more likely to not be getting enough sleep. Not sleeping enough is a major risk factor for depression, so if smartphones are causing less sleep, that alone could explain why depression and suicide increased so suddenly.

Depression and suicide have many causes.

Genetic predisposition, family environments, bullying and trauma can all play a role.

Some teens would experience mental health problems no matter what era they lived in.

But some vulnerable teens who would otherwise not have had mental health issues may have slipped into depression due to too much screen time, not enough face-to-face social interaction, inadequate sleep or a combination of all three.

It might be argued that it’s too soon to recommend less screen time, given that the research isn’t completely definitive. However, the downside to limiting screen time – say, to two hours a day or less – is minimal. In contrast, the downside to doing nothing – given the possible consequences of depression and suicide – seems, to me, quite high.

It’s not too early to think about limiting screen time; let’s hope it’s not too late.

For full references and the rest of this article please use the source link below.

Article source: BusinessInsider.com

U.S. Government Debt Increases are Unsustainable

Link to Original Article 

Do Not Tap Button; Economy May Instantly Collapse.

As the stock market continues to rise on the back of some of the worst geopolitical, financial, and domestic news, the U.S. Treasury has been quietly increasing the amount of government debt, with virtually no coverage by the Mainstream or Alternative Media.  So, how much has the U.S. debt increased in the past few days?   A bunch.

The surge in U.S. debt that took place over the past two days all started when the debt ceiling limit was officially allowed to increase on Sept 8th.  In just one day, the U.S. Treasury increased the public debt by $318 billion:

(chart courtesy of TreasuryDirect.gov)

The was the first time in U.S. history that the public debt rose over $20 trillion.  I mentioned this in my article, The U.S. Government Massive ONE-DAY Debt Increase Impact On Interest Expense & Silver ETF:

The U.S. Treasury will have to pay out an additional $7 billion interest payment for the extra $318 billion in debt it increased in just one day.  Again, that $7 billion interest payment is based on an average 2.2% rate multiplied by the $318 billion in debt.  Now, if we compare the additional $7 billion of U.S. interest expense to the total value of the silver SLV ETF of $5.8 billion, we can plainly see that printing money, and increasing debt becomes a valuable tool for Central Banks to cap the silver price.

Thus, when the U.S. Treasury increased the public debt by $318 billion, it will also have to pay an additional $7 billion in an annual interest payment to finance that debt.  However, that large one-day debt increase was over three weeks ago.  What’s been going on at the U.S. Treasury since then?  Let’s just say; they have been very busy… LOL.

On the last update in September, the U.S. Treasury increased the debt by nearly $40 billion on the very last day of the month:

(chart courtesy of TreasuryDirect.gov)

As we can see, the U.S. public debt increased from $20,203 billion ($20.203 trillion) on Sept. 28th to $20,245 billion on Sept 29th.  Overall, the U.S. debt increased $83 billion more since the $318 billion one-day increase on Sept 8th.   Which means, the total debt increase was $400 billion in a little more than three weeks.  However, the U.S. Government must be making up for lost time when the debt ceiling was frozen from March 15th to Sept 7th.

According to TreasuryDirect.gov website, the U.S. public debt ballooned by another $100 billion in the first two days of October:

(chart courtesy of TreasuryDirect.gov)

Alright, it only increased by $99 billion from $20,445 billion to $20,344 billion, but I’d rather use $100 billion because it has a better ring to it.  So, in less than a month, the U.S. Government public debt increased by a stunning $500 billion.  Along with the half trillion Dollars worth of new public debt, the U.S. Treasury will have to pay an additional $11 billion a year in interest payments based on an average 2.2% rate.

The notion that the Fed will continue to increase interest rates and begin to liquidate its inventory of MBS – Mortgaged Backed Securities that no one wanted in 2009-2010, as well as some of its high-quality Treasury toilet paper, is pure bollocks when they are handing out money hand over fist.  As I mentioned in my article linked above, if the interest rate went back to the 6.4% rate as it was in 2000, the U.S. Treasury interest on the debt would surge to more than $1.3 trillion.

Thus, our annual interest payment of $1.3 trillion (based on a 6.4% average interest rate) would account for one-third of the $3.9 trillion 2016 budget.  Of course, this could not fly as our annual deficit would jump from $587 billion (2016) to $1.4 trillion.  Actually, I believe we are going to see a $1+ trillion annual deficits in the next several years.

It is impressive to see how quick the U.S. Treasury is increasing the public debt:

Again, this additional $182 debt increase comes after the $318 billion one-day increase on Sept 8th.  No wonder, China and Russia are working together on alternative Gold-Backed Yuan Oil trading benchmark as highlighted in the article, A Failing Empire, Part 2: De-Dollarisation – China and Russia’s Plan From Petroyuan To Gold:

For China, Iran, and Russia, as well as other countries, de-dollarization has become a pressing issue.

The number of countries that are beginning to see the benefits of a decentralized system, as opposed to the US dollar system, is increasing.

  1. Iran and India, but also Iran and Russia, have often traded hydrocarbons in exchange for primary goods, thereby bypassing American sanctions.
  2. Likewise, China’s economic power has allowed it to open a 10-billion-euro line of credit to Iran to circumvent recent sanctions.
  3. Even the DPRK seems to use cryptocurrencies like bitcoin to buy oil from China and bypass US sanctions.
  4. Venezuela (with the largest oil reserves in the world) has just started a historic move to completely renounce selling oil in dollars, and has announced that it will start receiving money in a basket of currencies without US dollars. (This is not to mention the biggest change to have occurred in the last 40 years).
  5. Beijing will buy gas and oil from Russia by paying in yuan, with Moscow being able to convert yuan into gold immediately thanks to the Shanghai International Energy Exchange.

As the U.S. Treasury and Federal Government continues printing money and increasing its debt by $500 billion at a clip, the rest of the world is no longer going to sit around and wait for the negative ramifications.

Lastly, I have one more interesting chart to share before I conclude this article.  I find it quite ironic (HILARIOUS) that the gold and silver price PEAKED on the very same day the debt ceiling was increased and another $318 billion of debt was added to the U.S. Govt balance sheet while the Dow Jones Index bottomed and surged by 1,000+ points:

I gather this chart wraps up the situation nicely.  As the U.S. Govt pumps up the market with another $500 billion in debt, the stock market continues to move into BUBBLE TERRITORY.  Unfortunately, precious metals investors have to be patient until the Fed and U.S. Treasury completely BLOW UP the market.

Check back for new articles and updates at the SRSrocco Report.

U.s. Debt Clock, U.s. Debt Ceiling 2017, U.s. Debt Chart, U.s. Debt Crisis, U.s. Debt Right Now

Bitcoin Gold for the At-Home-Enthusiast!

Will Bitcoin Gold Return Power to Ordinary Users?

Original Article By Darryn Pollock on Cointelegraph

Will Bitcoin Gold Return Power to Ordinary Users?

Before the dust has even settled on Bitcoin’s civil war, which saw an acrimonious disagreement about how Bitcoin should handle its scaling debate, the major digital currency could be splitting again.

Bitcoin Cash was threatened, laughed off, created, boomed, and them fizzled out as Bitcoin carried on its merry mooning way, now with more capacity because of SegWit. Bitcoin Cash was the alternative to SegWit where blocks were blown up to monstrous proportions.

Bitcoin Gold, as the new potential hard forking currency will be called, is now an attempt to wrest the lucrative mining component of Bitcoin out of the hands of the giant firms that have monopolised the creation of the digital currency.

The people’s fork?

The new fork, set to reach landfall on October 25, is aiming to democratize mining. Mining farms and pools hold all the cards within Bitcoin, both as a voting demographic and as manipulators of things like price and fees.

Bitcoin Gold wants to see at-home enthusiast miners back in control. The project was apparently co-founded by Jack Liao, CEO of Hong Kong-based Bitcoin mining company LightningASIC. LightningASIC also conveniently sells the hardware that this new market of miners will need.

This fork seems to be a reaction to the general hatred that is flung towards Chinese mining giant Bitmain who, along with their controversial leader Jihan Wu, had a big part in the creation of Bitcoin Cash.

It must also be noted that Bitcoin Gold is different from another fork that is scheduled for November: Segwit2x. The November fork is aimed at increasing the capacity of the network where as the Bitcoin Gold split is looking to cut more people in on the mining pie.

A change in the hash

It used to be that mining was totally open to anyone who felt like firing up the software on their home computer. However, over time, Bitcoin mining became relegated to expensive custom miners operated in giant factories to achieve economies of scale.

Bitcoin Gold is changing their proof of work algorithm to Equihash, something fans of Zcash will be familiar with. It’s a “memory-hard” algorithm, which means common home computer hardware like GPUs will be able to profitably mine Bitcoin Gold for the foreseeable future.

Red flags

Bitcoin Gold is somewhat enigmatic at the moment, mostly because there is no technical information available anywhere. This is pretty strange, and quite disconcerting seeing as it is meant to go live this month.

Bitcoin Gold will also have the same address format as Bitcoin, and Bitcoin Cash, and this has already caused problems. There have been reports of people sending huge sums to wrong addresses – e.g. Bitcoin being sent to Bitcoin Cash wallets.

Finally, it should be noted that we use the word “fork” lightly. As Bitcoin Gold has essentially zero chance of replacing Bitcoin in the marketplace, it’s more of an air-drop than a chain split. Everybody that owns Bitcoin will also own Bitcoin Gold once the network goes live, but transactions on the Bitcoin Gold network won’t affect Bitcoin’s network, or vice versa.

More Bitcoin Gold Info to Come…

Bitcoin Gold Fork, Bitcoin Gold Price, Bitcoin Gold Exchange, Bitcoin Gold Hard Fork

How the Bitcoin Bubble Can Burst

There’s a cartoon currently popping up in the inboxes of Mayfair’s bitcoin-obsessed hedge fund managers. It’s titled ‘how to be an analyst’ and the hedgies are poking fun at their financier ‘inferiors’. When the digital currency rises in value, the analyst declares it a ‘bubble headed for a crash’. When it falls, it’s ‘bitcoin’s dead!’ The value’s flat? ‘No return on investment’. And if bitcoin’s price moves, it’s ‘too volatile’. The bitcoin believers are mocking the way cryptocurrency sceptics find fault whatever happens.

All of which illustrates how split the City is over bitcoin. Some herald it as a ‘monetary revolution’; others decry it as a boom about to go bust. Earlier this month, Jamie Dimon, chief executive of JP Morgan, declared the currency a ‘fraud’, arguing that it should only appeal ‘if you were in North Korea… a drug dealer or a murderer’. At the Barclays’ financial conference in New York, he said, ‘If we had a trader who traded bitcoin, I’d fire him in a second,’ sending bitcoin’s price down 6 per cent. He proclaimed it ‘worse than tulip bulbs’, a reference to the tulip mania in the Dutch golden age. Meanwhile, Chinese regulators have ordered all digital currency exchanges to close and banned fundraising through initial coin offerings (ICOs). The central bank warned that cryptocurrencies are being used ‘as a tool in criminal activities such as money-laundering and drug-trafficking’.

Could the most famous cryptocurrency be headed for a crash? The likes of Dimon arguably have a vested interest in bitcoin failing. ‘As the boss of one of the biggest banks in the world, why would he like anything that reduced his control over the money supply?’ says one hedge fund manager and bitcoin fan. A further concern is how in vogue bitcoin is. In the late Nineties, before the dotcom crash, celebrities piled in to internet start-ups that mostly ended up going bust. Now, Paris Hilton is taking part in a fundraising for digital token LydianCoin, while bra baroness Michelle Mone has said she will accept bitcoin as payment for lavish Dubai flats.

Outside the financial world, bitcoin remains little understood. Notably, Google’s auto-complete suggestions for ‘is bitcoin…?’ are ‘safe’ and ‘legal’. What makes people pay attention, though, are headlines like this: ‘If you bought $100 of bitcoin seven years ago, you’d be sitting on $72.9 million now’.

Jamie Dimon, is a skeptic (Bloomberg via Getty Images)

So what exactly is this magical money tree?

Bitcoin is the grandaddy of thousands of other cryptocurrencies. It was released in 2009 by an individual under the pseudonym Satoshi Nakamoto. Speculation abounds about who he actually is — the late computer developer Hal Finney and computer scientist Nick Szabo were touted as possibilities, though both denied it. It’s a virtual payment network, not unlike Paypal, except with no owner. Instead, computers across the globe process transactions and keep a shared ledger (a ‘blockchain’) that enables different contracts to occur. It has its own currency, bitcoin, the unit in which the network carries out transactions. Getting your hands on bitcoin is relatively straightforward: you can buy them on an exchange, as you would any other currency (one is worth around £3,000), or you could accept them for goods and services. But you can also ‘mine’ new ones — like mining gold, except instead of digging it out of the ground, you are rewarded with bitcoins by using your computer to verify other bitcoin transactions.

What is Bitcoin?

With bitcoin, the money supply is controlled by the computers. That means it doesn’t require a central bank, so there’s no Bank of England printing money (hence the Twitter meme with the Queen looking irked: ‘Tried Bitcoin. Didn’t have my face on it’). That prize keeps shrinking, meaning there’s a finite supply. Circulation is limited to 21 million by 2140, although each one can be subdivided into millions of pieces. Every bitcoin is accounted for in the ledger, so you cannot get a counterfeit.

You spend them in the same way you would spend other currencies. Contrary to perception, bitcoins are traceable — you can see which internet addresses every bitcoin has been at — but the owners’ names are encrypted. As of 2015, 100,000 vendors, including The Pembury Tavern in Hackney and Nincomsoup café in Old Street station, accepted bitcoin as payment. There’s even a church in Gospel Oak that accepts it for its collection. It is now so mainstream that a £1.65 million Peckham townhouse has just become the first UK property that can be bought using the digital currency, and there are ‘bitcoin ATMs’ (including one in the Londis on King’s Road).

Mark Karpelès (Bloomberg via Getty Images)

The irony of the debate over a bubble is that bitcoin was born just six weeks after Lehman Brothers went bust, as people searched for an alternative to the existing monetary system. It had its roots in the Julian Assange-backed ‘cypherpunks’ movement of the Nineties, in which activists argued the internet would create a new world outside the nation state. The conversation had died down until the financial crisis resurrected it. The first transaction came in 2010, when computer programmer Laszlo Hanyecz persuaded someone to accept 10,000 bitcoins he’d ‘mined’ in exchange for two pizzas. It came to be embraced by libertarians as a way, like gold, to store wealth. Silicon Valley then joined the bitcoin crypto-rush, interested both in the technology and its potential as a way to raise cash.

bitcoin ATM, at a King’s Road Londis

Bitcoin has, however, been hit by crisis and scandal. It first entered mainstream consciousness as the currency of the Silk Road, the online black market where drugs were sold. Two major bitcoin names have also ended up in court. Charlie Shrem, who set up Bitinstant (in which the Winklevoss twins invested), went to prison after being convicted of aiding and abetting an unlicensed money transmitting business, a charge related to the Silk Road. Meanwhile, Mark Karpelès, former head of what was once the world’s biggest bitcoin exchange, Mt Gox, was charged in Tokyo with embezzlement and data manipulation after Mt Gox collapsed in 2014.

‘I reject the idea that [cryptocurrencies] are only used by criminals and terrorists,’ says Arthur Hayes, the co-founder of BitMEX, a bitcoin derivatives exchange based in Hong Kong. ‘The real currencies that finance terrorism and crime are the dollar and the euro. The cryptocurrency movement will only expand. It is a digital currency version of “I don’t trust the government”; the analogue version being gold.’

It has emerged that even JP Morgan has routed customer orders for bitcoin-related instruments, although the bank does not take positions on this with its own cash. Emad Mostaque, co-chief investment officer at hedge fund Capricorn Fund Managers in Mayfair, says, ‘I can bet you JP Morgan’s wealth customers are asking, “Why don’t I have bitcoin?” It doesn’t move with other assets, so it’s a good hedge.’ Mostaque adds that savers can even buy bitcoin in their ISA: ‘If you could put one per cent of your ISA in it, and it can return 10 times that or it can collapse, what would you do?’

The main worry about bitcoin, Mostaque explains, is initial coin offerings, the latest financial fad. ICOs are where ‘tokens’ in a new digital currency that promise future goods and services are sold as a way for a company to raise cash. This is where it starts to look like a bubble. Ethereum is a cryptocurrency, but also a platform for apps, allowing developers to sell a stake in the app by issuing tokens with ICOs. In June, one raised $30,000 in half an hour; purchasers were buying a token called ‘F***’ (described as ‘a social cryptocurrency that aims to help everyone around the world give a F***’). There’s even a prostitution cryptocurrency, Lust, for sex workers and their customers.

Arthur Hayes, co-founded a bitcoin derivatives exchange (Bloomberg via Getty Images)

‘ICOs are like when companies floated in 1999 with a website address and a smile,’ says one Square Mile cynic. ‘Same thing, different way to throw your money away. People are basically selling air.’ Scammers can use blockchain technology to create ICOs that perhaps look promising but are essentially flimflam. More than £1.3 billion has been raised in ICOs this year. Where is the money coming from? Analysts say it is often from those who bought bitcoin on the cheap some years ago and are now millionaires. The UK watchdog, the Financial Conduct Authority, warned that anyone thinking of buying coins in an ICO should only do so if they are prepared to lose everything. One banker likened it to the South Sea Bubble of the 1700s, where a company bought up the rights to trade in the South Seas, then sold shares in its company which eventually become worthless.

There are echoes of other crises too. In 1929, millionaire Joe Kennedy sold his stocks after a shoe-shiner gave him share tips, the theory being that by the time the boy on the street is telling you what to buy, values have become inflated. The Wall Street crash followed. ‘This time, it’s bankers hearing their teenage nephew has bought bitcoin,’ says that same sceptic.

So what’s the problem with bitcoin? ‘The main issue is that established currencies have a legal footing in each country whereas bitcoin doesn’t,’ says a banker who asked not to be named. ‘Governments can clamp down on trading in it, like in China, saying it is circumventing capital controls.’

Crypto crib: the Peckham townhouse available to buy with bitcoin (© Munday’s / SWNS)

Governments have reason to fear bitcoin. It removes the role of government as the central issuer of money — and guarantor that money is real. As another banker notes: ‘There’s a huge amount of power in controlling the money supply, such as using quantitative easing to pump cash into the economy. All the Western economies are based around an ever-increasing money supply. Bitcoin has a fixed supply of currency — that hasn’t ended well in the past, like when Britain came off the gold standard in the 1930s. If a government can’t print more money, it can’t run a budget deficit.’ As the founder of the Rothschild banking dynasty probably didn’t actually say: ‘Give me control of a nation’s money and I care not who makes its laws.’ This is why China — where most of the biggest bitcoin miners are — has cracked down heavily on cryptocurrencies. ‘China is afraid of anything it can’t control,’ Hayes explains. ‘But it can’t stop people using bitcoin — you can’t shut off the internet.’

Bitcoin’s fans argue it will have the most profound uses in countries where the money system is broken, such as in Zimbabwe and Venezuela. It could also benefit the 2.5 billion adults who don’t have bank accounts, and enable immigrants to send remittances home more cheaply than services like Western Union do. As such, fans believe bitcoin could help create a more equal world. ‘In the region we work in — emerging economies — banks don’t provide services for the majority,’ says Hayes. ‘Bitcoin allows people to invest, to participate in a global phenomenon.’

Michelle Mone, is accepting bitcoin for Dubai flats (WireImage)

When the central bank of Cyprus seized savings, citizens downloaded bitcoin apps on their phones. Others believe Brexit could make bitcoin take off in Britain — although it’s probably too expensive to trade (there’s an $8 transaction fee, so you’re not using it to buy a Starbucks mocha). Still, the technology is likely to become more sophisticated, ironing out flaws and making a future cryptocurrency viable — a bitcoin 2.0. If there is a crash, something sustainable could emerge from the wreckage.

That could still be used for nefarious purposes. In Lionel Shriver’s most recent novel, The Mandibles, she envisaged a dystopian future in which the US experiences hyperinflation due to a newly created international reserve cryptocurrency.

READ MORE HERE…

Cryptocurrencies And Blockchain, Cryptocurrencies Bubble, Cryptocurrencies China, Cryptocurrencies For Beginners, Cryptocurrencies How They Work

Digital ‘Currencies’ Are ALL A Scam (via The Market Ticker)

For those who don’t understand how Bitcoin, or any other crypto-currencies are perceived as a scam, here is an article from The Market Ticker. Comments at the end of the article source are also worth reading.

Read More at the Source: The Market Ticker

A quick primer for those who don’t understand how these work.

Digital “currencies” are all basically the same. There is a finite number of a given “coin” type at inception; each has a cryptographic “key” that must be discovered in order to “acquire” it, which the proponents argue is similar to digging it out of the ground, and thus it is called “mining” them.

However, each successive coin in a given currency is harder to “mine” than the previous one; the cryptographic series is designed intentionally this way. The first few coins are easy and they get more difficult as the number of them mined is a greater percentage of the whole. The designer attempts to slightly outpace the growth rate of processor capability to solve said problem so that (1) it’s reasonably practical to “mine” them at the outset but (2) as time goes on it becomes more difficult at a fast enough rate that the stock of said coins is not completely exhausted at any given time, NOR does it become so prohibitively difficult that there is no point in trying.

The “coins” are designed to be “self-proving” through a technology known as “blockchain” in the generic sense. In order to confirm your coin is valid (and owned by you) others must reproduce your published “signing” result on the coin you claim to have mined. In addition to prevent your “coin” (which is just a series of bits — that is, a number) from being duplicated (counterfeited) whenever you exchange it with someone else they have to sign the “coin” and that transaction has to be published and the signature verified by some number of others before the “spend” is considered to be good. Once it is considered good then ownership of said coin has passed to the new person. Through this mechanism, the transfer of a given coin – from its mining onward – can be irrevocably traced and it is thus impossible (in theory anyway) for someone to duplicate (counterfeit) said coin.

Digital “coins” are divisible and such divisions are just as valid as an original, but again a division must be confirmed and signed as well. Thus you can spend 1/10th of a coin, the person who has 1/10th can spend half of that (or 1/20th of the original) and so on.

The design of these systems, however, is intentionally deflationary. That is, not only is it harder and harder to “mine” more coins but any coin in which the signature cannot be confirmed because the person who last signed it loses their signing key is irrevocably lost.

There are nuances between all the different “coins” but they all share a common set of problems:

While the number of a given coin is distinct, discrete and finite there is no limit to the number of competing digital “coins.” If you don’t like the ones that are present today you can set up another one and nothing prevents you (or someone else) from doing so. This means that the common chestnut of there being a “finite supply” is false.

A deflationary “currency” over time ultimately becomes extinct and valueless. In order for something to have a price it must in some form or fashion, for some period of time store value. The creators of digital currencies try to insure this through their deflationary design.

The problem is that in order to get the value out of a non-physical thing that thing must be a medium of exchange. That in turn requires wide acceptance by various individuals and firms transacting in that coin in some fashion.

As the number of coins in circulation inevitably decreases due to its deflationary design it ultimately must lose individuals and firms willing to transact in same. At some critical mass point it becomes crippled sufficiently in terms of exchange that the alleged “value” collapses.

Alleged “exchanges” have no clean business model. A valid exchange must exist solely on fees charged for transactions. The problem is that a distributed authentication model, which is what makes “blockchain” work, inherently has no means for the validating nodes to charge back the work of validation to the transacting parties. This results in those nodes having to exist via some other means (e.g. mining), and that means is usually speculating on the coins themselves! If you want to know why these exchanges seem to have a record of absconding with your coins (or “losing” them), this is the reason — they have no legitimate business model to otherwise pay for the continuing daily costs of validating and transacting between parties.

ALL such “digital currencies” are by design and intent a means to separate you from wealth and give it to whoever founded said “currency.” They are for this reason all effectively a pyramid scheme. This will inevitably lead to the seizure and closing of all such systems — if and when governments figure it out. The reason is simple: With a finite and ever-more-difficult means of mining each successive coin the effect on value for participants is exactly the same as it is in any pyramid scheme. Since nothing of physical existence is created or dug out of the ground there is no utility value and thus no floor price, unlike gold or silver (both of which have industrial value due to the metallurgical properties.) The person who “invents” such a system gets to “mine” many coins at very low cost (in electricity or whatever.) He then watches the “value” of said coins escalate as each one becomes harder to “mine” and as hype takes over, and can convert that “wealth” into some other form, whether it be a fiat currency, real property or otherwise. The founder always makes a grossly outsized “profit” in this fashion with the available profit dropping exponentially and ratably in every single case simply based on the number of participants. At the beginning recruiting others who also make money is easy because mining the coins is easy. However, over time recruiting others becomes harder and harder.

This is exactly identical to what happens in a traditional pyramid scheme — the founder gets a cut off all the sales from everyone under him. The next layer who all find the field “un-mowed” with lots of customers make a lot of money too, but always less than the first group and so on. But since the number of customers is finite, just as is the number of coins, with each successive layer of participants it gets harder and harder to find others to transact in sufficient volume to turn a profit because the acquisition of each new (coin or customer) becomes exponentially more-difficult. It is thus impossible on a mathematical basis for any such design to be self-sustaining since it relies on an exponentially more difficult act in a finite world. ALL such systems are inherently ponzi schemes whether we are talking about digital currencies or the alleged sale of products.

This doesn’t mean you can’t try to speculate in such “currencies”, because you certainly can. However, you must recognize a few things before doing so.

First, it is my contention that you are probably participating in an illegal scheme, albeit one that is not currently recognized as such by the authorities. No matter the instance, design, product or service any exponentially more-difficult (with time or number of “wins” or “participants”) system is inherently a pyramid scheme. That is it will always result in less return for the second participant than the first, for the third than the second, and so on. Eventually the return will always become negative at which point the scheme collapses. This is mathematically provable and is why such schemes are supposed to be illegal everywhere. Part of your risk profile assessment thus must include whether such digital currency schemes will be ruled an illegal pyramid scheme by governing authorities somewhere (or everywhere) and if it is whether you will simply lose all the money you put into it or worse, potentially be criminally prosecuted.

Second, because blockchain inherently records every transaction for each “mined item” back to its point of origin the risk of that loss through said action never disappears. Cryptographic signatures are admissible evidence since they are very close to being absolutely tamper-proof and as a result if such an outcome occurs the risk of a forcible unwind of any transfer out of said “currency” into some other form of money or property never expires.

Third, any attempt to evade paying taxes on any gains you make in such “currencies” is idiotic because your ownership and the exact P&L on your transactions is not only trivially able to be determined it is published in the blockchain and visible to anyone who cares to look! If you don’t declare every penny of such gains and a government decides to look they can trivially nail you and since there is no statute of limitations on intentional tax fraud in the United States (only on errors) you can get hammered retroactively literally for the rest of your life.

Fourth, because there is no means of payment to the validators of transactions from those who do transact due to the distributed design any “coins” you have at an exchange are subject to being lost or stolen if said exchange is unable to fund itself, and many of those exchanges, if not most, must be presumed to be speculating on the increasing price of said “coins” as their primary means of funding. With the “miners” being validators (which is true for, I believe, all existing systems) this adds a second level of risk in that they can quit too since they don’t get paid for validating — only for discovering “new” coins. This exposes you to an insane amount of business risk over which you have no control. In addition you must contend with all the other risks associated with third-party custody of anything such as theft or destruction. Since a coin is non-duplicable and if stolen, spent and validated (or worse deleted) it is irretrievably gone such risks are exactly the same as those involved in holding a bar of gold or stack of $20 bills. We have existing insurance systems for physical storage of various items of value for other things, but I am aware of none that are worth a bucket of spit when it comes to digital currency exchanges. This may change in the future but for now it makes any holding of such “coins” by a third party extremely risky.

Fifth, because all such systems are self-extinguishing in that they are deflationary by intent and eventually either run out of coins to mine or cost more to mine one than the value that can be obtained through their exchange the number of persons willing to continue to provide validation of transactions as an uncompensated “part of their operation” (that otherwise makes money, e.g. by mining) eventually falls to zero. Along with this the ever-increasing size of the transaction chain that must be maintained this makes the computational cost of validation as coins are divided and subdivided become ever-larger. Ultimately this forces some sort of payment model into the validation system but that’s not a solution either as the larger and larger size of said chain causes the cost to continually increase without boundary. Somewhere well before there are either zero validators or the cost of validation exceeds the marginal value of your proposed transaction you will lose the critical mass necessary to validate transactions in a reasonable amount of time and with reasonable certainty at which point said “digital currency” becomes worthless. Nobody knows exactly where this “knee point” is for any given instance but that this problem exists by design in every case is a fact.

So go ahead and play if you wish folks, but just recognize that you’re riding a ponzi scheme — and that all of them, without exception, eventually collapse.

How Much Does the Internet Weigh?

This is certainly the lengthiest post I’ve ever curated from another source – but I wanted to collect all of the information in one place to show, figuratively, how much the weight of the internet is gaining. Tables are reproduced here, but the Figures (or images attributions noted) are on the original website. Original source for the article is here: The Zettabyte Era

This is from an article updated in June 2016 titled. My question is: how will this relentless march toward reaching the physical limits of broadcasting capabilities impact marketing and advertising? You don’t believe there are limits? Do a search and discovery on how the 5G network will affect our brains.

The Zettabyte Era — Trends and Analysis – Cisco

This document is part of the Cisco® Visual Networking Index (VNI), an ongoing initiative to track and forecast the impact of visual networking applications. The document presents some of the main findings of Cisco’s global IP traffic forecast and explores the implications of IP traffic growth for service providers. For a more detailed look at the forecast and the methodology behind it, visit Cisco VNI: Forecast and Methodology, 2015–2020.

Executive Summary

Annual global IP traffic will pass the zettabyte ([ZB]; 1000 exabytes [EB]) threshold by the end of 2016, and will reach 2.3 ZB per year by 2020. By the end of 2016, global IP traffic will reach 1.1 ZB per year, or 88.7 EB per month, and by 2020 global IP traffic will reach 2.3 ZB per year, or 194 EB per month.

Global IP traffic will increase nearly threefold over the next 5 years. Overall, IP traffic will grow at a compound annual growth rate (CAGR) of 22 percent from 2015 to 2020. Monthly IP traffic will reach 25 GB per capita by 2020, up from 10 GB per capita in 2015.

Busy-hour Internet traffic is growing more rapidly than average Internet traffic. Busy-hour (or the busiest 60‑minute period in a day) Internet traffic increased 51 percent in 2015, compared with 29-percent growth in average traffic. Busy-hour Internet traffic will increase by a factor of 4.6 between 2015 and 2020, and average Internet traffic will increase by a factor of 2.0.

Smartphone traffic will exceed PC traffic by 2020. In 2015, PCs accounted for 53 percent of total IP traffic, but by 2020 PCs will account for only 29 percent of traffic. Smartphones will account for 30 percent of total IP traffic in 2020, up from 8 percent in 2015. PC-originated traffic will grow at a CAGR of 8 percent, and TVs, tablets, smartphones, and machine-to-machine (M2M) modules will have traffic growth rates of 17 percent, 39 percent, 58 percent, and 44 percent, respectively.

Traffic from wireless and mobile devices will account for two-thirds of total IP traffic by 2020. By 2020, wired devices will account for 34 percent of IP traffic, and Wi-Fi and mobile devices will account for 66 percent of IP traffic. In 2015, wired devices accounted for the majority of IP traffic, at 52 percent.

Content delivery networks (CDNs) will carry nearly two-thirds of Internet traffic by 2020. Sixty-four percent of all Internet traffic will cross CDNs by 2020 globally, up from 45 percent in 2015.

The number of devices connected to IP networks will be more than three times the global population by 2020. There will be 3.4 networked devices per capita by 2020, up from 2.2 networked devices per capita in 2015. There will be 26.3 billion networked devices in 2020, up from 16.3 billion in 2015.

Broadband speeds will nearly double by 2020. By 2020, global fixed broadband speeds will reach 47.7 Mbps, up from 24.7 Mbps in 2015.

Global Internet Video and Gaming Highlights

It would take more than 5 million years to watch the amount of video that will cross global IP networks each month in 2020. Every second, a million minutes of video content will cross the network by 2020.

Globally, IP video traffic will be 82 percent of all IP traffic (both business and consumer) by 2020, up from 70 percent in 2015. Global IP video traffic will grow threefold from 2015 to 2020, a CAGR of 26 percent. Internet video traffic will grow fourfold from 2015 to 2020, a CAGR of 31 percent.

Internet video surveillance traffic nearly doubled in 2015, from 272 petabytes per month at the end of 2014 to 516 petabytes per month in 2015. Internet video surveillance traffic will increase tenfold between 2015 and 2020. Globally, 3.9 percent of all Internet video traffic will be due to video surveillance in 2020, up from 1.5 percent in 2015.

Virtual reality traffic quadrupled in 2015, from 4.2 petabytes (PB) per month in 2014 to 17.9 PB per month in 2015. Globally, virtual reality traffic will increase 61-fold between 2015 and 2020, a CAGR of 127 percent.

Internet video to TV grew 50 percent in 2015. This traffic will continue to grow at a rapid pace, increasing 3.6-fold by 2020. Internet video to TV will be 26 percent of fixed consumer Internet video traffic in 2020.

Consumer video-on-demand (VoD) traffic will nearly double by 2020. The amount of VoD traffic in 2020 will be equivalent to 7.2 billion DVDs per month.

Internet gaming traffic will grow sevenfold from 2015 to 2020, a CAGR of 46 percent. Globally, Internet gaming traffic will be 4 percent of consumer Internet traffic in 2020, up from 2 percent in 2015.

Global Mobile Highlights

Globally, mobile data traffic will increase eightfold between 2015 and 2020. Mobile data traffic will grow at a CAGR of 53 percent between 2015 and 2020, reaching 30.6 exabytes per month by 2020.

Global mobile data traffic will grow almost three times as fast as fixed IP traffic from 2015 to 2020. Fixed IP traffic will grow at a CAGR of 19 percent between 2015 and 2020, while mobile traffic grows at a CAGR of 53 percent. Global mobile data traffic was 5 percent of total IP traffic in 2015, and will be 16 percent of total IP traffic by 2020.

Regional Highlights

IP traffic is growing fastest in the Middle East and Africa, followed by Asia Pacific. Traffic in the Middle East and Africa will grow at a CAGR of 41 percent between 2015 and 2020.

Summary of regional growth rates:

  • IP traffic in North America will reach 59.1 EB per month by 2020, growing at a CAGR of 19 percent.
  • IP traffic in Western Europe will reach 28.0 EB per month by 2020, growing at a CAGR of 20 percent.
  • IP traffic in Asia Pacific will reach 67.8 EB per month by 2020, growing at a CAGR of 22 percent.
  • IP traffic in Latin America will reach 11.6 EB per month by 2020, growing at a CAGR of 21 percent.
  • IP traffic in Central and Eastern Europe will reach 17.0 EB per month by 2020, growing at a CAGR of 27 percent.
  • IP traffic in the Middle East and Africa will reach 10.9 EB per month by 2020, growing at a CAGR of 41 percent.

Note:    Several interactive tools are available to allow you to create custom highlights and forecast charts by region, by country, by application, and by end-user segment (refer to the Cisco VNI Forecast Highlights tool and the Cisco VNI Forecast Widget tool).

Global Business Highlights

Business IP traffic will grow at a CAGR of 18 percent from 2015 to 2020. Increased adoption of advanced video communications in the enterprise segment will cause business IP traffic to grow by a factor of 2 between 2015 and 2020.

Business Internet traffic will grow at a faster pace than IP WAN. IP WAN traffic will grow at a CAGR of 6 percent, compared with a CAGR of 21 percent for fixed business Internet and 47 percent for mobile business Internet traffic.

Business IP traffic will grow fastest in the Middle East and Africa. Business IP traffic in the Middle East and Africa will grow at a CAGR of 21 percent, a faster pace than the global average of 18 percent. In volume, Asia Pacific will have the largest amount of business IP traffic in 2019, at 11.4 EB per month. North America will be second, at 9.1 EB per month.

Forecast Overview

The current Cisco Visual Networking Index (VNI) forecast projects global IP traffic to nearly triple from 2015 to 2020. Appendix A offers a detailed summary. Overall IP traffic is expected to grow to 194 EB per month by 2020, up from 72.5 EB per month in 2015, a CAGR of 22 percent (Figure 1). This growth represents only a slight tapering from last year’s projected growth rate for 2014 to 2019, which was 23 percent. It appears that global IP traffic growth is stabilizing in the 20–25 percentage range.

Figure 1.      Cisco VNI Forecasts 194 EB per Month of IP Traffic by 2020

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

For more details about Cisco’s forecasting methodology, refer to the paper “Cisco VNI: Forecast and Methodology, 2015–2020.”

To understand the magnitude of IP traffic volumes, it helps to look at the numbers in more familiar terms:

  • By 2020, the gigabyte (GB) equivalent of all movies ever made will cross the global Internet every 2 minutes.
  • Globally, IP traffic will reach 511 terabits per second (Tbps) in 2020, the equivalent of 142 million people streaming Internet high-definition (HD) video simultaneously, all day, every day.
  • Global IP traffic in 2020 will be equivalent to 504 billion DVDs per year, 42 billion DVDs per month, or 58 million DVDs per hour.

Total Internet traffic has experienced dramatic growth in the past two decades. More than 20 years ago, in 1992, global Internet networks carried approximately 100 GB of traffic per day. Ten years later, in 2002, global Internet traffic amounted to 100 gigabytes per second (GBps). In 2015, global Internet traffic reached more than 20,000 GBps. Table 1 provides a view of the historical benchmarks for total Internet traffic.

Table 1.       The Cisco VNI Forecast—Historical Internet Context

Year Global Internet Traffic
1992 100 GB per day
1997 100 GB per hour
2002 100 GBps
2007 2,000 GBps
2015 20,235 GBps
2020 61,386 GBps

Source: Cisco VNI, 2016

 

Per capita IP and Internet traffic growth has followed a similarly steep growth curve over the past decade. Globally, monthly IP traffic will reach 25 GB per capita by 2020, up from 10 GB per capita in 2015, and Internet traffic will reach 21 GB per capita by 2020, up from 7 GB per capita in 2015. Not long ago, in 2008, per capita Internet traffic was 1 GB per month. In 2000, per capita Internet traffic was 10 megabytes (MB) per month.

The sections that follow explore the trends contributing to the continued growth of global IP traffic.

Trend 1: Continued Shifts in Mix of Devices and Connections

Figure 2 shows that globally, devices and connections (10-percent CAGR) are growing faster than both the population (1.1-percent CAGR) and Internet users (6.5-percent CAGR). This trend is accelerating the increase in the average number of devices and connections per household and per Internet user. Each year, various new devices in different form factors with increased capabilities and intelligence are introduced and adopted in the market. A growing number of M2M applications, such as smart meters, video surveillance, healthcare monitoring, transportation, and package or asset tracking, are contributing in a major way to the growth of devices and connections. By 2020, M2M connections will be 46 percent of the total devices and connections.

Figure 2.      Global Devices and Connections Growth

Figures (n) refer to 2015, 2020 device share.

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

M2M connections will be the fastest-growing category, growing nearly 2.5- fold during the forecast period, at 20‑percent CAGR, to 12.2 billion connections by 2020. Smartphones will grow the second fastest, at 13-percent CAGR (increasing by a factor of 1.8). Connected TVs (which include flat-panel TVs, set-top boxes, digital media adapters [DMAs], Blu-ray disc players, and gaming consoles) will grow nearly next fastest at 12-percent CAGR, to 3.1 billion by 2020. PCs will continue to decline (about a 2-percent decline) over the forecast period. However, there will more PCs than tablets by the end of 2020 (1.35 billion PCs vs. 785 million tablets).

By 2020 the consumer share of the total devices, including both fixed and mobile devices, will be 74 percent, with business claiming the remaining 26 percent. Consumer share will grow at a slightly slower rate, at 9.5-percent CAGR relative to the business segment, which will grow at 12-percent CAGR. For more details about the growth in devices and connections in residential, consumer mobile, and business segments, refer to the Cisco VNI Service Adoption Forecast Highlights tool.

Globally, the average number of devices and connections per capita will grow from 2 in 2015 to 3.2 by 2020 (Table 2).

Table 2.       Average Number of Devices and Connections per Capita

2015 2020 CAGR
Asia Pacific  1.87 2.82 8.5 %
Central and Eastern Europe 2.49 3.96 9.8%
Latin America 2.07 2.95 7.4%
Middle East and Africa 1.09 1.47 6.2%
North America 7.14 12.18 11.3%
Western Europe 5.09 8.87 11.7%
Global 2.21 3.39 8.9%

Source: Cisco VNI, 2016

 

Among the countries that will have the highest average of per capita devices and connections by 2020 are the United States (12.3), South Korea (12.2), and Japan (11.9).

The changing mix of devices and connections and growth in multidevice ownership affects traffic and can be seen in the changing device contribution to total IP traffic. At the end of 2015, 47 percent of IP traffic and 37 percent of consumer Internet traffic originated from non-PC devices. By 2020, 71 percent of IP traffic and 71 percent of consumer Internet traffic will originate from non-PC devices (Figure 3).

Figure 3.      Global IP Traffic by Devices

Figures (n) refer to 2015, 2020 device share.

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

As in the case of mobile networks, video devices can have a multiplier effect on traffic. An Internet-enabled HD television that draws 45 minutes of content per day from the Internet would generate as much Internet traffic as an entire household today. With the growth of video viewing on smartphones and tablets, traffic from these devices is growing as a percentage of total Internet traffic. Tablets will account for 15 percent of total global Internet traffic by 2020, up from 9 percent in 2015. Smartphones will account for 37 percent of total global Internet traffic by 2020, up from 11 percent in 2015 (Figure 4).

Figure 4.      Global Internet Traffic by Device Type

Figures (n) refer to 2015, 2020 device share.

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

The video impact of the devices on the traffic is more pronounced because of the introduction of ultra-high-definition (UHD), or 4K, video streaming. This technology has such an impact because the bit rate for 4K video at about 18 Mbps is more than double the HD video bit rate and nine times more than standard-definition (SD) video bit rate. We estimate that by 2020, 40 percent of the installed flat-panel TV sets will be UHD, up from 8 percent in 2015 (Figure 5).

Figure 5.      Increasing Video Definition: By 2020, More Than 40 Percent of Connected Flat-Panel TV Sets Will Be 4K

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

UHD (or 4K) IP VoD will account for 21 percent of global VoD traffic in 2020 (Figure 6).

Figure 6.      Global 4K Video Traffic

Figures (n) refer to 2015, 2020 traffic shares.

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

Trend 2: IPv6 Adoption Enables Internet of Everything Connectivity

The transition from an IPv4 environment to an IPv6 environment is making excellent progress, with increases in IPv6 device capabilities, content enablement, and operators implementing IPv6 in their networks. These developments are particularly important because Asia, Europe, North America, and Latin America have already exhausted their IPv4 allotments, and Africa is expected to exhaust its allotment by 2018.

Table 3 shows the projected exhaustion dates as of May 2016, according to the Regional Internet Registries (RIR).

Table 3.       IPv4 Address Exhaustion Dates

Regional Internet Registries Exhaustion Date
Asia Pacific Network Information Centre (APNIC) April 19, 2011 (actual)
Réseaux IP Européens Network Coordination Centre (RIPE NCC) September 14, 2012 (actual)
Latin America and Caribbean Network Information Centre (LACNIC) June 10, 2014 (actual)
American Registry for Internet Numbers (ARIN) September 24, 2015 (actual)
African Network Information Center (AFRINIC) April 4, 2018 (projected)

 

Building on the VNI IPv6-capable devices analysis, the forecast estimates that globally there will be nearly 13 billion IPv6‑capable fixed and mobile devices by 2020, up from nearly 4 billion in 2015, a CAGR of 27 percent. In terms of percentages, 48 percent of all fixed and mobile networked devices will be IPv6-capable by 2020, up from 23 percent in 2015 (Figure 7).

This estimate is based on the capability of the device and the network connection to support IPv6, and is not a projection of active IPv6 connections. Mobile-device IPv6 capability is assessed based on OS support of IPv6 and estimations of the types of mobile network infrastructure to which the device can connect (3.5-generation [3.5G] or later.) Fixed-device IPv6 capability is assessed based on device support of IPv6 and an estimation of the capability of the residential customer premises equipment (CPE) or business routers to support IPv6, depending on the device end-user segment.

Figure 7.      Global IPv6-Capable Devices and Connections Forecast 2015–2020

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

Globally, 90 percent of smartphones and tablets will be IPv6-capable by 2020, up from 60 percent in 2015. Globally, there will be 5.8 billion IPv6-capable smartphones and tablets by 2020, up from 2.1 billion in 2015. By 2020, 30 percent of M2M connections will be IPv6-capable, reaching 3.7 billion, a 67-percent CAGR.

According to the World IPv6 Launch Organization in May 2016, fixed and mobile network operators worldwide are deploying IPv6 and starting to report notable IPv6 traffic generation. Romania’s RCS & RDS reported nearly 12 percent, France’s Free Telecom reported 22 percent, KDDI reported nearly 28 percent, Comcast reported 45 percent, AT&T reported 59 percent, and Verizon Wireless reported 69 percent deployment. According to Google, in May 2016 the percentage of users who access Google through IPv6 is about 11 percent.

Amid these industry developments, the VNI forecast is undertaking an effort to estimate the potential IPv6 network traffic that could be generated if a percentage of IPv6-capable devices become actively connected to an IPv6 network, given the estimated global average for monthly traffic per device type.

Looking to 2020, if 60 percent of IPv6-capable devices are actively connected to an IPv6 network, the forecast estimates that globally IPv6 traffic would amount to 55 EB per month, or 34 percent of total Internet traffic (Figure 8).

Figure 8.      Projected Global Fixed and Mobile IPv6 Traffic Forecast 2015–2020

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

This initial estimation of potential IPv6 traffic is based on the assumptions that IPv6 device capability, IPv6 content enablement, and IPv6 network deployment will keep pace with current trends, and may even accelerate during the forecast period. Considering the interdependence of these variables, forecast assumptions could be subject to refinement as our analysis continues.

Content providers are also moving to increase the IPv6 enablement of their sites and services. According to Cisco IPv6 labs, by 2020 the content available over IPv6 will be about 35 percent. There can be, however, variation depending on the popularity of websites across regions and countries. In addition, specific country initiatives and content-provider deployments have positively affected local IPv6 content reachability.

Overall, the likelihood that a significant portion of Internet traffic will be generated over IPv6 networks holds considerable opportunity for network operators, content providers, and end users seeking to gain the scalability and performance benefits of IPv6 and enable the Internet of Everything (IoE).

Trend 3: M2M Applications Across Many Industries Accelerate IoE Growth

The Internet of Everything (IoE) phenomenon, in which people, processes, data, and things connect to the Internet and each other, is showing tangible growth. Globally, M2M connections will grow nearly 2.5-fold, from 4.9 billion in 2015 to 12.2 billion by 2020 (Figure 9). There will be 1.6 M2M connections for each member of the global population by 2020.

Figure 9.      Global M2M Connection Growth

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

Connected home applications, such as home automation, home security and video surveillance, connected white goods, and tracking applications, will represent 47 percent, or nearly half, of the total M2M connections by 2020, showing the pervasiveness of M2M in our lives (Figure 10). Connected healthcare, with applications such as health monitors, medicine dispensers, first-responder connectivity, and telemedicine, will be the fastest-growing industry segment, at 49-percent CAGR. Connected car applications will have the second-fastest growth, at 37-percent CAGR. Chips for pets and livestock, digital health monitors, and numerous other next-generation M2M services are promoting this growth.

Figure 10.    Global M2M Connection Growth by Industries

* Other includes Agriculture, Construction, and Emergency Services.

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

Although the number of connections is growing threefold, global M2M IP traffic will grow sixfold over this same period, from one EB per month in 2015 (1.4 percent of global IP traffic) to 6.3 EB by 2020 (3.2 percent of global IP traffic; refer to Figure 11). The amount of traffic is growing faster than the number of connections because of the increase of deployment of video applications on M2M connections and the increased use of applications, such as telemedicine and smart car navigation systems, which require greater bandwidth and lower latency.

Figure 11.    Global M2M Traffic Growth: Exabytes per Month

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

Trend 4: Service Adoption Trends: Residential, Consumer Mobile, and Business Services

Global Residential Services: Video Continues to Grow

Between 2014 and 2015, the highest growth happened on the Internet side in online gaming, with 15-percent year‑over-year (YoY) growth. Social networking was the most widely adopted residential Internet service, with YoY growth of 8.5 percent, growing from 1.3 billion users in 2014 to 1.4 billion users in 2015.

By 2020, digital TV and social networking will be the two services with the highest penetration rates, with 87 percent and 76 percent, respectively. The fastest growth will come from time-delayed TV services such as personal video recorder (PVR) and digital video recorder (DVR) services, at 7-percent CAGR. Online gaming (5.3-percent CAGR) will be the fastest-growing residential Internet service. Online gaming growth is accelerated primarily by technology enhancements in PCs such as graphics, motion sensing, gesture recognition, etc. (Figure 12).

Figure 12.    Global Residential Services Adoption and Growth

Note: By 2020, the global residential fixed Internet population will be 2.4 billion; the number of global TV households will be 1.8 billion.

Source: Cisco VNI Service Adoption Forecast, 2015–2020

Global Consumer Mobile Services

Between 2014 and 2015, all consumer mobile services except one grew at more than 10 percent YoY. The highest growth was in consumer location-based services (LBS), with YoY growth of 38 percent, from a base of 585 million users in 2014 to 807 million in 2015. Other significant YoY growth was in mobile banking and commerce (37 percent), followed by mobile video (35 percent). Regions such as Latin America (62-percent YoY growth) and the Middle East and Africa (52-percent YoY growth) had the fastest growth in consumer mobile LBS. Mobile banking and commerce also grew the fastest in Latin America, at 49-percent YoY growth. Mobile video growth was led by Middle East and Africa, at 43-percent YoY growth.

From 2015 to 2020, six out of eight consumer mobile services will grow at more than 14-percent CAGR, three will grow at more than 20-percent CAGR, and one will decline. The fastest growth will be in consumer LBS (3.9 percent), followed by mobile commerce (22.7 percent). Regions with especially high rates of growth in mobile commerce services are the Middle East and Africa, Central and Eastern Europe, Latin America, and Asia Pacific, which have historically been underserved (or not reached) by traditional brick‑and-mortar financial institutions (Figure 13).

Figure 13.    Global Consumer Mobile Services Adoption and Growth

Note: By 2020, the global consumer mobile population will be 5 billion.

Source: Cisco VNI Service Adoption Forecast, 2015–2020

Global Business Services

Between 2014 and 2015, the highest YoY growth was in business LBS, with a 32-percent increase, from 92 million users in 2014 to 121 million in 2015. Other significant YoY growth was in desktop video conferencing (25 percent; refer to Figure 14).

Business LBS includes services used by corporate subscribers in which the subscription is generally paid by the employer. These services include salesforce and field-force automation, fleet management, etc.

We see that personal or desktop video conferencing is increasingly replacing room-based conferencing as video becomes simpler and more integrated into unified communications business service offers.

From 2015 to 2020, the fastest-growing business service is expected to be desktop or personal video conferencing. The growth in personal video conferencing, specifically unified communications–based video conferencing, has recently accelerated because of the higher quality and lower price of new services and products. It is also caused by the availability of desktop video conferencing offers, which can be standalone or integrated. In addition, the growth in mobile clients will support video conferencing growth. Conversely, the use of web conferencing without video will show a decline of 4-percent CAGR over the forecast period (Figure 14).

Figure 14.    Global Business Services Adoption and Growth

Note: By 2020, the global business Internet population will be 2.2 billion; the number of business users will be 577 million.

Source: Cisco VNI Service Adoption Forecast, 2015–2020

 

For details about all aspects of the service adoption study, use the Cisco VNI Service Adoption Highlights tool.

Trend 5: Applications Traffic Growth

The sum of all forms of IP video, which includes Internet video, IP VoD, video files exchanged through file sharing, video-streamed gaming, and video conferencing, will continue to be in the range of 80 to 90 percent of total IP traffic. Globally, IP video traffic will account for 82 percent of traffic by 2020 (Figure 15).

Figure 15.    Global IP Traffic by Application Category

Figures (n) refer to 2015, 2020 traffic shares.

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

The implications of video growth are difficult to overstate. With video growth, Internet traffic is evolving from a relatively steady stream of traffic (characteristic of peer-to-peer [P2P] traffic) to a more dynamic traffic pattern.

In the past year, service providers have observed a pronounced increase in traffic associated with gaming downloads. Newer consoles such as the Xbox One and PlayStation 4 have sufficient onboard storage to enable gamers to download new games rather than buy them on disc. These graphically intense games are large files, and gaming downloads are already 2 percent of consumer fixed Internet traffic, and will reach 4 percent of consumer fixed Internet traffic by 2020. Furthermore, these downloads tend to occur during peak usage periods, with gaming downloads reaching up to 10 percent of busy-hour traffic.

Impact of Video on Traffic Symmetry

With the exception of short-form video and video calling, most forms of Internet video do not have a large upstream component. As a result, traffic is not becoming more symmetric, a situation that many expected when user-generated content first became popular. The emergence of subscribers as content producers is an extremely important social, economic, and cultural phenomenon, but subscribers still consume far more video than they produce. Upstream traffic has been slightly declining as a percentage for several years.

It appears likely that residential Internet traffic will remain asymmetric for the next few years. However, numerous scenarios could result in a move toward increased symmetry; for example:

  • Content providers and distributors could adopt P2P as a distribution mechanism. There has been a strong case for P2P as a low-cost content-delivery system (CDS) for many years, yet most content providers and distributors have opted for direct distribution, with the exception of applications such as PPStream and PPLive in China, which offer live video streaming through P2P and have had great success. If content providers in other regions follow suit, traffic could rapidly become highly symmetric.
  • High-end video communications could accelerate, requiring symmetric bandwidth. PC-to-PC video calling is gaining momentum, and the nascent mobile video calling market appears to have promise. If high-end video calling becomes popular, traffic could move toward greater symmetry.

Generally, if service providers provide ample upstream bandwidth, applications that use upstream capacity will begin to appear.

Trend 6: “Cord-Cutting” Analysis

In the context of the VNI Forecast, “Cord-cutting” refers to the trend in which traditional and subscription television viewing is increasingly being supplanted by other means of video viewing, such as online and mobile video, which are available to viewers through fixed and mobile Internet connections.

We are seeing a trend in which the growth in digital television service that denotes television viewing across all digital platforms (cable, IPTV, satellite, etc.) is growing much more slowly relative to mobile video (Figure 16). This trend is more pronounced in regions such as North America and Western Europe, where the penetration of digital TV is already high. Online video, which we found was growing faster until last year, is now growing almost at par with digital television. Also, in emerging regions mobile video growth rates are even higher, because these regions are skipping over fixed connectivity.

Figure 16.    Mobile Video Growing Fastest; Online Video and Digital TV Grow Similarly

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

Another factor supporting this trend is that the total addressable markets for these services—residential Internet users, consumer mobile users, and total TV households (for digital-TV households)—show significantly different growth patterns (Figure 17). Residential Internet users are expected to increase at a CAGR of nearly 3.2 percent, and consumer mobile users at 2.8 percent, while at the same time the number of TV households is flattening, with a meager 1.8-percent forecasted CAGR.

Figure 17.    Growth in Global Residential Internet Users Compared to Growth in Global TV Households

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

Also, if we look at Internet devices such as digital media adapters (DMAs), we find that although they represent only 9 percent of all Internet connected set-top boxes (STBs)—including, service provider STBs, gaming consoles, and directly connected Internet TV sets—by 2020 they will represent 32 percent of global Internet STB traffic. This trend again shows that there is increasingly less reliance on STBs managed by service providers for Internet access in general and for video specifically (Figure 18).

Figure 18.    Growth in Global Digital Media Adapters

* DMAs include devices such as Roku, Apple TV, Chromecast, etc.

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

From a traffic perspective, we expect that on average a household that is still on linear TV will generate much less traffic than a household that has “cut the cord” and is relying on Internet video (Figure 19). A cord-cutting household will generate 102 GB per month in 2016, compared to 49 GB per month for an average household. This difference occurs because linear television generates much less traffic (one stream of video shared across numerous linear-TV households) than Internet video, which is unicast to each Internet video device.

Figure 19.    Global Cord Cutting Generates Double the Traffic

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

Trend 7: Security Analysis

Users expect their online experience to be always available and always secure—and for their personal and business assets to be safe. Annual security reports for 2016 from industry giants in the security space highlight the need for increased focus on cybercrimes, data breaches and espionage, and mitigation strategies (Figure 20).

Figure 20.    Security—Industry Top of Mind

 

The last several years have been easily the most eventful period from a security threat perspective, with many serious data breaches that have been discussed widely in the media. There were a total of 780 breaches with a total of nearly 178 million records stolen in 2015. The number of records stolen per data breach averaged 228 thousand in 2015, according to 2015 data breach statistics from IDT911. The average cost paid for each sensitive lost or stolen record increased 6 percent from 2015 to 2016, according to a joint study by IBM and Ponemon Institute.

More secure Internet servers leads to a large footprint of security and authentication, better serving end users with secure transactions and communication. The percentage of secure Internet servers that conduct encrypted transactions over the Internet using Secure Sockets Layer (SSL) compared to the total number of web-facing servers depicts the nature of the secure footprint. Western Europe led with the number of secure Internet servers per 1 million people with 50 percent, followed by Central and Eastern Europe with 29 percent, North America with 27 percent, and Asia Pacific with around 23 percent. The average number of breaches was highest in Asia Pacific organizations and lowest in U.K. and U.S. enterprises in 2015, according to a recent study published by McAfee.

Sixty percent of data stolen was through web protocols, file transfer and tunneling protocols, or email. Two-thirds of breaches involved traditional corporate networks, and cloud break-ins accounted for the remaining one-third, according to McAfee and LemonFish (Figure 21).

Figure 21.    How Is Data being Breached?

Source: McAfee, Lemonfish, Cisco VNI 2016

 

Frequency of distributed denial-of-service (DDoS) attacks has increased more than 2.5 times over the last 3 years, according to Arbor Networks. DDoS attacks are increasing at roughly the same rate as traffic. Peak DDoS attack size (Gbps) is increasing in a linear trajectory, with peak attacks reaching 300, 400, and 500 Gbps respectively, in 2013, 2014, and 2015, at about 10 to 15 percent per year. DDoS attacks can represent up to 10 percent of a country’s total Internet traffic while they are occurring. The average size of DDoS attacks is increasing steadily and approaching 1 Gbps, enough to take most organizations completely off line. In 2015 the top motivation behind DDoS attacks was criminals demonstrating attack capabilities, with gaming and criminal extortion attempts in second and third place, respectively. DDoS attacks account for more than 5 percent of all monthly gaming-related traffic and more than 30 percent of gaming traffic while they are occurring.

The events from 2015 and the first quarter of 2016 once again demonstrated that the attackers are increasing their computing resources to perform DDoS attacks. Amplification attackers, who have tools for carrying out a DDoS attack, exploit vulnerabilities in the network and compute resources. With the growth of the IoE and spread of vulnerable devices and traditional PCs, the abundance of configuration drawbacks with applications can be targeted. Security vendors continue to ensure these attacks are financially unviable for the cybercriminals. Globally the number of DDoS attacks grew 25 percent in 2015 and will increase 2.6-fold to 17 million by 2020 (Figure 22).

Figure 22.    Global DDoS Attacks Forecast, 2015-2020

Figures (n) refer to 2015, 2020 traffic shares.

Source: Cisco VNI Global IP Traffic Forecast, 2015-2020

Trend 8: Impact of Accelerating Speeds on Traffic Growth

Fixed Speeds

Broadband speed is a crucial enabler of IP traffic. Broadband-speed improvements result in increased consumption and use of high-bandwidth content and applications. The global average broadband speed continues to grow and will nearly double from 2015 to 2020, from 24.7 Mbps to 47.7 Mbps. Table 4 shows the projected broadband speeds from 2015 to 2020. Several factors influence the fixed broadband-speed forecast, including the deployment and adoption of fiber to the home (FTTH), high-speed DSL, and cable broadband adoption, as well as overall broadband penetration. Among the countries covered by this study, Japan, South Korea, and Sweden lead within the VNI countries in terms of broadband speed largely because of their wide deployment of FTTH.

Table 4.       Fixed Broadband Speeds (in Mbps), 2015–2020

Region 2015 2016 2017 2018 2019 2020 CAGR
(2015–2020)
Global  24.7  29.5  32.8  38.5  43.5  47.7 14%
Asia Pacific  28.1  33.9  37.4  41.5  46.8  51.3 13%
Latin America  7.6  9.3  11.3  13.6  16.2  17.8 18%
North America  25.4  32.9  37.6  42.7  47.4  51.4 15%
Western Europe  22.8  30.2  35.5  41.2  46.0  50.1 17%
Central and Eastern Europe  25.3  29.2  32.8  36.6  41.2  46.3 13%
Middle East and Africa  7.0  7.8  9.2  12.8  14.8  16.5 19%

Source: Cisco VNI, 2016

 

Consider how long it takes to download an HD movie at these speeds: at 10 Mbps, it takes 20 minutes; at 25 Mbps, it takes 9 minutes; but at 100 Mbps, it takes only 2 minutes. High-bandwidth speeds will be essential to support consumer cloud storage, making the download of large multimedia files as fast as a transfer from a hard drive. Table 5 shows the percentage of broadband connections that will be faster than 10 Mbps, 25 Mbps, and 100 Mbps by region.

Table 5.       Broadband Speed Greater Than 10 Mbps, 2015–2020

Region Greater Than 10 Mbps Greater Than 25 Mbps Greater Than 100 Mbps

2015

2020

2015

2020

2015

2020

Global 53% 77% 30% 38% 4% 8%
Asia Pacific 53% 83% 30% 52% 4% 8%
Latin America 27% 39% 10% 15% 1% 2%
North America 64% 88% 38% 52% 5% 9%
Western Europe 54% 74% 32% 43% 5% 11%
Central and Eastern Europe 58% 83% 33% 41% 3% 6%
Middle East and Africa 17% 20% 7% 8% 0.3% 1%

Source: Cisco VNI, 2016

 

There is a strong correlation between experienced speeds and number of video minutes viewed per viewer (Figure 23). As speeds increase in each country covered in the study, the number of video minutes per viewer also increases.

Figure 23.    Increase in Experienced Speeds (Mbps) Increases Internet Video Viewership (Minutes)—2016

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

Mobile Speeds

Globally, the average mobile network connection speed in 2015 was 2.0 Mbps. The average speed will more than double and will be 6.5 Mbps by 2020. Smartphone speeds, generally third-generation (3G) and later, are currently nearly three times higher than the overall average. Smartphone speeds will nearly double by 2020, reaching 12.5 Mbps.

Anecdotal evidence supports the idea that overall use increases when speed increases, although there is often a delay between the increase in speed and the increased use, which can range from a few months to several years. The reverse can also be true with the burstiness associated with the adoption of tablets and smartphones, where there is a delay in experiencing the speeds that the devices can support. The Cisco VNI Forecast relates application bit rates to the average speeds in each country. Many of the trends in the resulting traffic forecast can be seen in the speed forecast, such as the high growth rates for developing countries and regions relative to more developed areas (Table 6).

Table 6.       Projected Average Mobile Network Connection Speeds (in Mbps) by Region and Country

2015 2016 2017 2018 2019 2020 CAGR
(2015–2020)

Global

Global speed: All handsets 2.0 2.4 3.1 3.9 5.1 6.5 26%
Global speed: Smartphones 7.5 8.3 9.2 9.9 11.1 12.5 11%
Global speed: Tablets 11.6 12.8 13.9 15.0 15.6 16.2 7%

By Region

Asia Pacific 2.4 3.6 4.6 5.7 7.0 8.6 29%
Latin America 1.5 1.9 2.5 3.1 3.9 4.9 27%
North America 5.9 7.9 9.9 12.1 13.7 15.3 21%
Western Europe 4.1 6.1 8.3 10.5 12.2 14.1 28%
Central and Eastern Europe 2.3 3.4 5.6 7.8 9.1 10.6 36%
Middle East and Africa 0.8 1.3 1.9 2.6 3.6 4.8 45%

Source: Cisco VNI Mobile, 2016

Current and historical speeds are based on data from Ookla’s Speedtest. Forward projections for mobile data speeds are based on third-party forecasts for the relative proportions of 2G, 3G, 3.5G, and 4G among mobile connections through 2020.

 

A crucial factor promoting the increase in mobile speeds over the forecast period is the increasing proportion of fourth-generation (4G) mobile connections. The impact of 4G connections on traffic is significant, because 4G connections, which include mobile WiMAX and Long-Term Evolution (LTE), generate a disproportionate amount of mobile data traffic.

Wi-Fi Speeds from Mobile Devices

Globally, Wi-Fi connection speeds originated from dual-mode mobile devices will nearly double by 2020. The average Wi-Fi network connection speed (10.6 Mbps in 2015) will exceed 18.5 Mbps in 2020. North America will experience the highest Wi-Fi speeds, 29 Mbps, by 2020 (Table 7).

Wi-Fi speeds inherently depend on the quality of the broadband connection to the premises. The speed also depends on the Wi-Fi standard in the CPE device. The latest standard, IEEE 802.11ac, is considered a true wired complement and can enable higher-definition video streaming and services that require higher data rates. Also an important factor in the use of Wi-Fi technology is the number and availability of hotspots.

Table 7.       Projected Average Wi-Fi Network Connection Speeds (in Mbps) by Region and Country

Region 2015 2016 2017 2018 2019 2020 CAGR (2015-2020)
Global  12.5  18.2  19.5  21.8  23.1  24.4 14%
Asia Pacific  11.4  19.5  20.9  22.3  23.5  24.7 17%
Latin America  5.9  7.7  8.4  9.2  9.9  10.6 12%
North America  17.4  27.4  29.2  31.5  33.6  35.5 15%
Western Europe  13.9  20.3  22.4  23.2  24.0  24.8 12%
Central and Eastern Europe  13.4  16.7  19.0  21.6  23.3  25.3 13%
Middle East and Africa  4.4  4.9  5.5  6.1  6.7  7.0 10%

Source: Cisco VNI, 2016

Trend 9: Mobility (Wi-Fi) Continues to Gain Momentum

Globally, there will be nearly 433 million public Wi-Fi hotspots by 2020, up from 64 million hotspots in 2015, a sevenfold increase. By 2020, China will lead in total number of hotspots, followed by the United States and France. Western Europe had 45 percent of the world’s Wi-Fi hotspots share in 2015. By 2020, public Wi-Fi along with community hotspots are accounted for as well. Community hotspots or homespots are just emerging as a potentially significant element of the public Wi-Fi landscape. In this model, subscribers allow part of the capacity of their residential gateway to be open to casual use. The homespot may be provided by a broadband or other provider directly or through a partner. Asia Pacific will lead in adoption of homespots. By 2020, China will lead in total number of homespots, followed by France and Japan. Adoption of homespots has been led by Western Europe and then North America in 2015, but Asia Pacific will lead by 2020.

Critical enablers of Hotspot 2.0 adoption are higher-speed Wi-Fi gateways and the adoption of the IEEE 802.11ac and 802.11n standards. Globally, the prevalence of IEEE 802.11ac, the latest Wi-Fi standard, will gain momentum from 2015 through 2020. In 2015, 59.5 percent of all home Wi-Fi routers shipped globally were 802.11ac-enabled. By 2020, 96.6 percent of all home Wi-Fi routers will be equipped with 802.11ac. IEEE 802.11n, which was ratified in 2007, provides a range of speeds that allow users to view medium-resolution video streaming because of the higher throughput. The latest standard, IEEE 802.11ac, with very high theoretical speeds, is considered a true wired complement and can enable higher-definition video streaming and services with use cases that require higher data rates (Figure 24).

Figure 24.    Future of Wi-Fi as Wired Complement

 

The rapid growth of mobile data traffic has been widely recognized and reported. The trend toward mobility carries over into the realm of fixed networks as well, in that an increasing portion of traffic will originate from portable or mobile devices. Figure 25 shows the growth in Wi-Fi and mobile traffic in relation to traffic from wired devices. By 2020, wired networks will account for 34 percent of IP traffic, and Wi-Fi and mobile networks will account for 66 percent of IP traffic. In 2015, wired networks accounted for the majority of IP traffic, at 52 percent; Wi-Fi accounted for 43 percent; and mobile or cellular networks accounted for 5 percent of total global IP traffic.

Figure 25.    Global IP Traffic, Wired and Wireless*

* Wireless traffic includes Wi-Fi and mobile.

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

Narrowing the focus to Internet traffic and excluding managed IP traffic yields a more pronounced trend. By 2020, wired devices will account for 22 percent of Internet traffic, and Wi-Fi and mobile devices will account for 78 percent of Internet traffic (Figure 26). In 2015, wired devices accounted for less than half of Internet traffic, at 38 percent.

Figure 26.    Global Internet Traffic, Wired and Wireless

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

Trend 10: Traffic-Pattern Analysis (Peak Compared to Average and CDN Uptake)

Although average Internet traffic has settled into a steady growth pattern, busy-hour traffic (or traffic in the busiest 60‑minute period of the day) continues to grow more rapidly. Service providers plan network capacity according to peak rates rather than average rates. In 2015, busy-hour Internet traffic grew 51 percent, and average traffic grew at 29 percent. Between 2015 and 2020, global busy-hour Internet use will grow at a CAGR of 36 percent, compared with 25 percent for average Internet traffic (Figure 27).

Video is the underlying reason for accelerated busy-hour traffic growth. Unlike other forms of traffic, which are spread evenly throughout the day (such as web browsing and file sharing), video tends to have a “prime time.” Because of video consumption patterns, the Internet now has a much busier busy hour. Because video has a higher peak-to-average ratio than data or file sharing, and because video is gaining traffic share, peak Internet traffic will grow faster than average traffic. The growing gap between peak and average traffic is amplified further by the changing composition of Internet video. Real-time video such as live video, ambient video, and video calling has a peak-to-average ratio that is higher than on-demand video.

Figure 27.    Busy-Hour Compared with Average Internet Traffic Growth

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

Changes in traffic topology are being brought about by the increasing role of content delivery networks (CDNs) in data delivery. CDNs will carry 64.5 percent of total Internet traffic by 2020 (Figure 28). Although network performance is usually attributed to the speeds and latencies offered by the service provider, the delivery algorithms used by CDNs have an equal if not more significant bearing on video quality.

Figure 28.    Global Content Delivery Network Internet Traffic, 2015 and 2020

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

Speed is a critical factor in Internet traffic. When speed increases, users stream and download greater volumes of content, and adaptive bit-rate streaming increases bit rates automatically according to available bandwidth. Service providers find that users with greater bandwidth generate more traffic. In 2015, households with high-speed fiber connectivity generated 58 percent more traffic than households connected by DSL or cable broadband, globally (Figure 29). The average FTTH household generated 68 GB per month in 2015 and will generate 138 GB per month in 2020.

Figure 29.    Fiber-Connected Households Generate More Traffic Than Households with Other Sources of Broadband

Source: Cisco VNI Global IP Traffic Forecast, 2015–2020

 

To limit the volume of traffic, service providers can institute use-based tiered pricing and data caps.

On mobile networks, by looking at the use of more than 33,000 lines from Tier-1 mobile operators from 2010 to 2015, we found that monthly traffic from the top 1 percent of users is down to 18 percent of overall use compared to 52 percent in 2010, showing the effects of tiered pricing. With mobile penetration reaching a saturation point in many countries across all regions, the trend has been toward tiered plans as a way to monetize data and effectively manage or throttle the top users of traffic. On the fixed networks, data caps continue to increase to match subscribers’ growing appetite for video. In the United States, Tier-1 carriers are offering a variety of fair usage limits today, as high as 1 TB per month. A large provider in Japan has a 30-GB-per-day upload cap. In several countries, Netflix has a sizable percentage of the Internet video minutes and traffic. Wildcard traffic generators such as Twitch.TV, a live streaming service in which video gamers watch each other play, has established itself on many fixed networks around the world.

Data caps affect a larger percentage of mobile users than fixed users. With Tier-1 carriers, approximately 12 percent of mobile users consume more than 2 GB per month (a common mobile data cap), whereas only 1.4 percent of fixed users consume more than 500 GB per month (a common fixed data cap).

Other Trends to Watch

Cisco’s approach to forecasting IP traffic is conservative, and certain emerging trends have the potential to increase the traffic outlook significantly.

  • Growth of smartphones as the “communications hub” for social media, video consumption, tracking IoE/digitization applications (et al.), as well as traditional voice. This trend demonstrates the impact that smartphones have on how consumers and businesses users access and use the Internet and IP networks.
  • Internet gaming is seeing a resurgence—the traffic nearly doubled in 2015 and will grow seven-fold by 2020. Gaming on demand and streaming gaming platforms have been in development for several years, with many newly released in 2014 and 2015. With traditional gaming, graphical processing is performed locally on the gamer’s computer or console. With cloud gaming, game graphics are produced on a remote server and transmitted over the network to the gamer. If cloud gaming becomes popular, gaming could quickly become one of the largest Internet traffic categories.
  • Virtual reality: With new hardware available to individuals, and a growing body of content to consume, virtual reality has experienced high growth in recent years. Traffic associated with virtual and augmented reality applications quadrupled in 2015 and is poised to grow 61-fold by 2020. This growth stems mainly from the download of large virtual reality content files and applications, but a significant wild card is the potential adoption of virtual reality streaming, which could raise our prediction of high-growth even higher.
  • Immersive video: This emerging traffic type can cause significant new network design implications as it is a high-bandwidth consuming application. Social media platforms such as Facebook have launched support for spherical, or immersive video that integrates multiple camera angles to form a single video stream and can be watched from the viewer’s preferred perspective. It can generate bit rates 3 to 10 times greater than non-immersive HD bit rates.
  • Video surveillance: New Internet-connected video surveillance cameras upload a constant video stream to the cloud for remote viewing. With a steady flow of video traffic from each camera, video surveillance is already having an impact on overall Internet traffic and accounts for 1.5 percent of total Internet traffic today, growing to nearly 4 percent by 2020. If such devices become mass market in the next five years, we could see video cameras generating a significantly higher volume of traffic, since Internet-enable cameras can produce up to 300 GB per camera per month for full HD-resolution monitoring of high-activity areas.

For More Information

For more information about the Cisco IP traffic forecast, refer to “Cisco VNI: Forecast and Methodology, 2015–2020” and visit the other resources and updates at www.cisco.com/go/vni. Several interactive tools allow you to  create custom highlights and forecast charts by region, country, application, and end-user segment. Refer to the Cisco VNI Highlights tool and the Cisco VNI Forecast Widget tool. For regional details about the VNI service adoption forecast, please visit the Cisco VNI SA highlights tool and Cisco VNI SA Graphing tool. Inquiries can be directed to traffic‑inquiries@cisco.com.

Appendix A: Cisco Global IP Traffic Forecast

Table 8 shows a summary of the Cisco global IP traffic forecast. For more information and additional tables, refer to “Cisco VNI: Forecast and Methodology, 2015–2020.”

Table 8.       Global IP Traffic, 2015–2020

IP Traffic, 2015–2020

2015

2016

2017

2018

2019

2020

CAGR
(2015–2020)

By Type (Petabytes [PB] per Month)

Fixed Internet  49,494  60,160  73,300  89,012  108,102  130,758 21%
Managed IP  19,342  22,378  25,303  28,155  30,750  33,052 11%
Mobile data  3,685  6,180  9,931  14,934  21,708  30,564 53%

By Segment (PB per Month)

Consumer  58,539  72,320  89,306  109,371  133,521  162,209 23%
Business  13,982  16,399  19,227  22,729  27,040  32,165 18%

By Geography (PB per Month)

Asia Pacific  24,827  30,147  36,957  45,357  55,523  67,850 22%
North America  24,759  30,317  36,526  43,482  50,838  59,088 19%
Western Europe  11,299  13,631  16,408  19,535  23,536  27,960 20%
Central and Eastern Europe  5,205  6,434  8,116  10,298  13,375  17,020 27%
Latin America  4,500  5,491  6,705  8,050  9,625  11,591 21%
Middle East and Africa  1,930  2,698  3,822  5,380  7,663  10,865 41%

Total (PB per Month)

Total IP traffic  72,521  88,719  108,533  132,101  160,561  194,374 22%

Source: Cisco VNI, 2016

Definitions

  • Consumer: Includes fixed IP traffic generated by households, university populations, and Internet cafés
  • Business: Includes fixed IP WAN or Internet traffic, excluding backup traffic, generated by businesses and governments
  • Mobile: Includes Internet traffic that travels over 2G, 3G, or 4G mobile access technology
  • Internet: Denotes all IP traffic that crosses an Internet backbone
  • Non-Internet IP: Includes corporate IP WAN traffic, IP transport of TV and VoD, and mobile “walled‑garden” traffic

Cell Phones and Cancer Risk (via National Cancer Institute)

A fact sheet that outlines the available evidence regarding use of cellular/mobile telephones and cancer risk.

There are three main reasons why people are concerned that cell phones (also known as “mobile” or “wireless” telephones) might have the potential to cause certain types of cancer or other health problems:

  • Cell phones emit radiofrequency energy (radio waves), a form of non-ionizing radiation, from their antennas. Tissues nearest to the antenna can absorb this energy.
  • The number of cell phone users has increased rapidly. As of December 2014, there were more than 327.5 million cell phone subscribers in the United States, according to the Cellular Telecommunications and Internet Association. This is a nearly threefold increase from the 110 million users in 2000. Globally, the number of subscriptions is estimated by the International Telecommunications Union to be 5 billion.
  • Over time, the number of cell phone calls per day, the length of each call, and the amount of time people use cell phones have increased. However, improvements in cell phone technology have resulted in devices that have lower power outputs than earlier models.
What is radiofrequency energy and how does it affect the body?

Radiofrequency energy is a form of electromagnetic radiation. Electromagnetic radiation can be categorized into two types: ionizing (e.g., x-rays, radon, and cosmic rays) and non-ionizing (e.g., radiofrequency and extremely low frequency, or power frequency). Electromagnetic radiation is defined according to its wavelength and frequency, which is the number of cycles of a wave that pass a reference point per second. Electromagnetic frequencies are described in units called hertz (Hz).

The energy of electromagnetic radiation is determined by its frequency; ionizing radiationis high frequency, and therefore high energy, whereas non-ionizing radiation is low frequency, and therefore low energy. The NCI fact sheet Electromagnetic Fields and Cancer lists sources of radiofrequency energy. More information about ionizing radiation can be found on the Radiation page.

The frequency of radiofrequency electromagnetic radiation ranges from 30 kilohertz (30 kHz, or 30,000 Hz) to 300 gigahertz (300 GHz, or 300 billion Hz).  Electromagnetic fields in the radiofrequency range are used for telecommunications applications, including cell phones, televisions, and radio transmissions. The human body absorbs energy from devices that emit radiofrequency electromagnetic radiation. The dose of the absorbed energy is estimated using a measure called the specific absorption rate (SAR), which is expressed in watts per kilogram of body weight.

Exposure to ionizing radiation, such as from x-rays, is known to increase the risk of cancer. However, although many studies have examined the potential health effects of non-ionizing radiation from radar, microwave ovens, cell phones, and other sources, there is currently no consistent evidence that non-ionizing radiation increases cancer risk (1).

The only consistently recognized biological effect of radiofrequency energy is heating. The ability of microwave ovens to heat food is one example of this effect of radiofrequency energy. Radiofrequency exposure from cell phone use does cause heating to the area of the body where a cell phone or other device is held (ear, head, etc.). However, it is not sufficient to measurably increase body temperature, and there are no other clearly established effects on the body from radiofrequency energy.

It has been suggested that radiofrequency energy might affect glucose metabolism, but two small studies that examined brain glucose metabolism after use of a cell phone showed inconsistent results. Whereas one study showed increased glucose metabolism in the region of the brain close to the antenna compared with tissues on the opposite side of the brain (2), the other study (3) found reduced glucose metabolism on the side of the brain where the phone was used.

Another study investigated whether exposure to the radiofrequency energy from cell phones affects the flow of blood in the brain and found no evidence of such an effect (4).

The authors of these studies noted that the results are preliminary and that possible health outcomes from changes in glucose metabolism are still unknown. Such inconsistent findings are not uncommon in experimental studies of the biological effects of radiofrequency electromagnetic radiation (5). Some contributing factors include assumptions used to estimate doses, failure to consider temperature effects, and lack of blinding of investigators to exposure status.

How is radiofrequency energy exposure measured in epidemiologic studies?

Epidemiologic studies use information from several sources, including questionnaires and data from cell phone service providers. Direct measurements are not yet possible outside of a laboratory setting. Estimates take into account the following:

  • How “regularly” study participants use cell phones (the number of calls per week or month)
  • The age and the year when study participants first used a cell phone and the age and the year of last use (allows calculation of the duration of use and time since the start of use)
  • The average number of cell phone calls per day, week, or month (frequency)
  • The average length of a typical cell phone call
  • The total hours of lifetime use, calculated from the length of typical call times, the frequency of use, and the duration of use
What has research shown about the possible cancer-causing effects of radiofrequency energy?

Radiofrequency energy, unlike ionizing radiation, does not cause DNA damage that can lead to cancer. Its only consistently observed biological effect in humans is tissue heating. In animal studies, it has not been found to cause cancer or to enhance the cancer-causing effects of known chemical carcinogens (68). The National Institute of Environmental Health Sciences (NIEHS), which is part of the National Institutes of Health (NIH), is carrying out a large-scale study in rodents of exposure to radiofrequency energy (the type used in cell phones). This investigation is being conducted in highly specialized labs that can specify and control sources of radiation and measure their effects. Preliminary results from this study were released in May 2016.

Researchers have carried out several types of epidemiologic studies to investigate the possibility of a relationship between cell phone use and the risk of malignant (cancerous) brain tumors, such as gliomas, as well as benign (noncancerous) tumors, such as acousticneuromas (tumors in the cells of the nerve responsible for hearing), most meningiomas(tumors in the meninges, membranes that cover and protect the brain and spinal cord), and parotid gland tumors (tumors in the salivary glands) (9).

In one type of study, called a case-control study, cell phone use is compared between people with these types of tumors and people without them. In another type of study, called a cohort study, a large group of people who do not have cancer at study entry is followed over time and the rate of these tumors in people who did and didn’t use cell phones is compared. Cancer incidence data can also be analyzed over time to see if the rates of cancer changed in large populations during the time that cell phone use increased dramatically. These studies have not shown clear evidence of a relationship between cell phone use and cancer. However, researchers have reported some statistically significantassociations for certain subgroups of people.

Three large epidemiologic studies have examined the possible association between cell phone use and cancer: Interphone, a case-control study; the Danish Study, a cohort study; and the Million Women Study, another cohort study.

  • InterphoneHow the study was done: This is the largest health-related case-control study of cell phone use and the risk of head and neck tumors. It was conducted by a consortium of researchers from 13 countries. The data came from questionnaires that were completed by study participants.

    What the study showed: Most published analyses from this study have shown no statistically significant increases in brain or central nervous system cancers related to higher amounts of cell phone use. One analysis showed a statistically significant, although modest, increase in the risk of glioma among the small proportion of study participants who spent the most total time on cell phone calls. However, the researchers considered this finding inconclusive because they felt that the amount of use reported by some respondents was unlikely and because the participants who reported lower levels of use appeared to have a slightly reduced risk of brain cancer compared with people who did not use cell phones regularly (5,10,11). Another recent analysis from this study found no relationship between brain tumor locations and regions of the brain that were exposed to the highest level of radiofrequency energy from cell phones (12).

Source: National Cancer Institute