Here’s a new exaflood metric for you — tweets per second.

From the Twitter blog:

Folks were tweeting 5,000 times a day in 2007. By 2008, that number was 300,000, and by 2009 it had grown to 2.5 million per day. Tweets grew 1,400% last year to 35 million per day. Today, we are seeing 50 million tweets per day—that’s an average of 600 tweets per second. (Yes, we have TPS reports.)

“Striving to Map the Shape-Shifting Net” – by John Markoff – The New York Times – March 2, 2010

“Data, data, everywhere” – The Economist – Special Report on Managing Information – February 25, 2010

“Managing the Exaflood” – American Association for the Advancement of Science – February 19, 2010

“Professors Find Ways to Keep Heads Above ‘Exaflood’ of Data” – Wired Campus – The Chronicle of Higher Education – February 24, 2010

So, you are asking, HMI? The UCSD team estimates that in 2008 outside of the workplace Americans consumed 3.6 zettabytes of information. That’s 3.6 x 10^21 bytes, or 3,600 billion billion.

Against

• James Assey – Executive Vice President, National Cable and Telecommunications Association
• Robert Quinn -  Senior Vice President-Federal Regulatory, AT&T
• Christopher Yoo – Professor of Law and Communication; Director, Center for Technology, Innovation, and Competition, UPenn Law

For

• Tim Wu – Coined the term “Network Neutrality”; Professor of Law, Columbia Law
  
• Brad Burnham – VC, Union Square Ventures
• Nicholas Economides – Professor of Economics, Stern School of Business, New York University.

I think the side opposing the resolution wins, hands down — no contest really — but see for yourself.

This video may be “1080p,” but the frame-rate is slow, and the video motion is thus not very smooth. George Ou estimates the bit-rate at 3.7 Mbps, which is not enough for real full-motion HD. But we’re moving quickly in that direction.

• Internet traffic growing at least 45% annually.
• Web video jumped to 52% of all Internet traffic from 42%.
• P2P, although still substantial, dropped more than any other application.
• Google, between 2007 and 2009, jumped from outside the top-ten global ISPs by traffic volume to the number 3 spot.
• Comcast jumped from outside the top-ten to number 6.
• Content delivery networks (CDNs) are now responsible for around 10% of global Internet traffic.
• This fast-changing ecosystem is not amenable to rigid rules imposed from a central authority, as would be the case under “net neutrality” regulation.

Conclusion

 Internet is at an inflection point

 Transition from focus on connectivity to content
– Old global Internet economic models are evolving
– New entrants are reshaping definition / value of connectivity

 New technologies are reshaping definition of network
– “Web” / Desktop Applications, Cloud computing, CDN

 Changes mean significant new commercial, security and engineering challenges

 This is just the beginning…

These conclusions and the data Arbor tracked and reported largely followed our findings, projections, and predictions from two years ago:

• “Estimating the Exaflood – The Impact of Video and Rich Media on the Internet – A ‘zettabyte’ by 2015?”
• “Unleashing the ‘Exaflood’”
• “The Coming Exaflood”

And an update from this spring:

• “Rapid Internet Traffic Growth Continues in U.S. and Around Globe”

Also see our analysis from last winter highlighting the evolution of content delivery networks — what my colleague George Gilder dubbed “storewidth” back in 1999 — and which Arbor now says is the fastest growing source/transmitter of Net traffic.

See this partial description of Starent’s top product:

It is a rare criticism of elite American university students that they do not think big enough. But that is exactly the complaint from some of the largest technology companies and the federal government.

At the heart of this criticism is data. Researchers and workers in fields as diverse as bio-technology, astronomy and computer science will soon find themselves overwhelmed with information. Better telescopes and genome sequencers are as much to blame for this data glut as are faster computers and bigger hard drives. . . .

Two years ago, I.B.M. and Google set out to change the mindset at universities by giving students broad access to some of the largest computers on the planet. The companies then outfitted the computers with software that Internet companies use to tackle their toughest data analysis jobs.

“It sounds like science fiction, but soon enough, you’ll hand a machine a strand of hair, and a DNA sequence will come out the other side,” said Jimmy Lin, an associate professor at the University of Maryland, during a technology conference held here last week.

The big question is whether the person on the other side of that machine will have the wherewithal to do something interesting with an almost limitless supply of genetic information.

At the moment, companies like I.B.M. and Google have their doubts.

For the most part, university students have used rather modest computing systems to support their studies. They are learning to collect and manipulate information on personal computers or what are known as clusters, where computer servers are cabled together to form a larger computer. But even these machines fail to churn through enough data to really challenge and train a young mind meant to ponder the mega-scale problems of tomorrow.

Correction: Exa-scale.

“If they imprint on these small systems, that becomes their frame of reference and what they’re always thinking about,” said Jim Spohrer, a director at I.B.M.’s Almaden Research Center.