Things just got really interesting in the mobile / wireless world. Verizon announced that they will over two categories of service by the end of 2008. One will continue to be its bundled handset service, and the other will be open to any device. This change brings Verizon Wireless in-line with the open networks that are available in Europe and Asia. The move will force T-Mobile, Sprint, and AT&T to consider offering similar services. (T-Mobile is already experimenting with allows users to make WiFi calls.) This announcement also may affect the upcoming 700MHz spectrum auction, as the FCC did not require open networks. I’m hoping that it will spur more innovation in the mobile space. Changes could happen quickly, we’ll have to wait and find out. I’m trying to stay optimistic.

Update: Techcrunch and GigaOM weigh in on the issue. A lot can happen in a year, and GigaOM is correct to be skeptical.

Images source: Wikimedia Commons, Matt Brim

The October issue of Discovery magazine has an article that piqued my interest, entitled, “This Man Wants to Control the Internet. And you should let him.” The man is Caltech professor, John Doyle, an expert in control theory. His field models dynamic physical systems, which includes things from a mechanical heart to space flight. The key idea is achieving a desired or steady state for one of these systems by taking current information about its state, and “feedback” that information to the system to make adjustments. These feedback system are mathematically modeled. When the system is non-linear and dynamic, for instance a airplane flying through wind currents, the mathematics required become quite sophisticated.

Doyle and his collaborator and fellow CalTech professor, Steven Low, have developed an improved protocol over TCP (or Transmission Control Protocol.) TCP describes how packets of data should be delivered and received over the Internet. FTP, email and WWW applications all rely on TCP. Using control theory, their protocol, FastTCP^TM, clocks the time a data packet takes to get to a final destination and make adjustments to optimize its stream of packets. Standard TCP does not take this extra information into account, and relies mostly on a strategy of monitoring lost packets. That is, packets that don’t make it to the finally destination. In the 2006 Supercomputing Network Bandwidth Challenge, they won it with a maximum throughput of 17 gigabits (a full-length movie) per second.

Improvements to the Standard TCP will be important in the coming years, as multimedia services (such as movies on demand) will increase the demand of the current network. Already, VOIP services do not use TCP, because packets sent using TCP cannot be received and sequenced fast enough for real time applications like phone calls.

Doyle and Low, along with Cheng Jin formed the startup, FastSoft, to sell products based on FastTCP^TM. However, they have trademarked their name and have submitted patents their technology. This is an important departure from the origins of the Internet, as no one owns that Standard TCP. Having to license or buy FastTCP^TM from FastSoft has implications to the future of the Internet, which could lead to its fragmentation.

Last month, at team from Indiana Univeristy, the Technische Universitaet Dresden, Rochester Institute of Technology, Oak Ridge National Laboratory and the Pittsburgh Supercomputing Center won the 2007 challenge. They achieved a peak transfer rate of 18.21 Gigabits/second and a sustained transfer rate of 16.2 Gigabits/second. It is not clear to me what kind of IP, the team from IU has on their technology. However, the received funding from the NSF, which may mean place of some or all of their research into the public domain.

Demands for bandwidth are only increasing. A complete overhaul of TCP is years ago, and involves incremental change, because the network at stake (that is, the Internet) is so important, which Doyle explain the Discover article. How we meet those demands is already controversial.

Susan Crawford notes that Comcast is already traffic shaping bits, by flagging packets by people using BitTorrent. (She also has a nice description of TCP in this post.) Meeting this growing need, the network can improve performance in various ways including: upgrading the infrastructure, such as laying fiber optic cable; improving data compression algorithms, and improving the protocols that control data traffic. In all these areas, the ownership and regulations of these technologies have huge implications on accessibility and adoption of the Internet. Although the Discover article’s title “this man wants to control the Internet” is a play on Doyle’s field of study, it raises an important point. Having public and private protocols may not only make parts of the inaccessible to each other, but further increase bandwidth as another form of economic inequality.

I’ve been slowing making my way through a very good book “Innovation and Incentives,” by Suzanne Scotchmer from UC Berkeley. I’ll close with a quote from her chapter on “Networks and Network Effects”:

“The protocols of the Internet and worldwide web were developed at public expense and put into the public domain. Given what turned out to be at stake, that is probably one of the most fortunate accidents in industrial history.”

I guess that is something to be thankful for the day before Thanksgiving. Gigaom is linking to an Xing site, which calculates the value of your network. Mine is over a million dollars. You enter in some demographic information and they describe the size of your network, and the frequency of contact. Of course, a figure like how many people do you speak to weekly is very hard to estimate, which makes me question this numbers and charts really mean.

In the gallery section, you can compare your network value with others by country and industry and age (which is the horizontal access.) This clever addition makes it competitive, and vastly more sticky and viral. But I’m not sure why we are seeing all the peaks and curves. I’m not sure how many people have submitted to this, so it might a few people might be outliners and causing spikes. Getting more data points might smooth out the curve, I guess I’ll check back later.

I attended a very good discussion at MobileCamp on Mobile Social Networks, which was run by Keith Erskine of padpaw. We ended up talking a lot about facebook, which seemed to be on a lot of people’s mind. When talking about Linkedin and Facebook, the overall vibe I got was that people liked keeping their social networks separate in all their various forms.

In terms of social netwoking sites, Linkedin was for business, and Facebook was for friends and family. Recent feature additions or announcements for upcoming features on both sites are making them look more like each other. Linkedin recently added a photo feature and plans on opening up their platform. Facebook added groups and has a limited profile features, which comes very close to allowing different groups to get different versions of your site (although it’s not quite here yet.) Even with these features, it seems as if the group wanted to keep them apart. (There was the sense in some people are reaching the limit on how many sites they wanted to maintain.) It seems easier to me to maintain one, rather than several. Although I guess people may not want to have all their data locked into one privately owned site. This point brought up protocol, standards, and Open Social, which I want to address in another post.

People often use different email addresses for work and personal use, I check a handful accounts everyday. Since getting my Blackberry, I can finally synch my computer and phone address books, which was a simple but powerful change. Now, all my devices share the same information and it is now stored in multiple places.

Recently, I’ve received work email through Facebook which complicates my email archiving system. Friends have invited me into Linkedin. Although some relationships are clearly defined as work or personal, social circles are usually not that discreet. Their edges are porous and overlap, and people migrate from one to another. What is also interesting is how the bucketing of people now can get directly verbalized. That is, accepting an invite to Linkedin from a co-worker and then denying the invite into Facebook.

Why do people like to keep their social circles separate some of the time and not others? It is a personal preference? Or are there user experiences (for lack of a better word) involved which have an effect if we want to group them together or not?

Image source: IEEE

Noah Brier posted an interesting link recently to an article claiming that Metcalfe’s Law, which famously has been paraphrased to be the value of a network exponentially quadratically grows with each additional node, is wrong. This is a provocative thesis because the law is widely trumpeted in all that is good about the Internet.

In the theoretical long term view, networks with more nodes will encourage late adopters to join (and pay.) People often cite the instance of email, the rates of people setting up (and paying for) email accounts in the 1990s rose much faster after it was possible to communication with people outside a user’s ISP, being AOL, Compuserve, Prodigy, or an academic institution. However, network adoptions plays out differently in other cases.

The disconnect here may be that in the definition of value, more specifically value by whom. In the valuation of a network, the network of 100 is worth more than a network of 10. According to Metcalfe, it’s worth 100 times (10^2) the smaller network. For the consumer, it is clear that the value of the telecommunications network grows with each new person, especially if the costs for the user doesn’t increase. However, consider combining access of two competing networks from the perspective of the network operators. From this angle, the smaller network will clearly see more benefit than that larger network, as the article suggests. Further, both operators will see an increase in the costs associated with network traffic (from hardware to customer service,) with no new paying customers. If the operators are charging an unlimited usage prices, there is little upside to combining networks, which shows why network operators tend to resist interoperability. Why would a market leading operator take on additional cost with increased revenue and help a smaller competitor?

Coming back to the definition of value, the value of the network actually doesn’t change if the willing to pay (i.e. the ability to extract fees) from the customers of the network. I’m still trying to grapple with the difference between the value of the network from the customer versus the operator. That is, the problem is that as although the value of a larger network may grow, there willingness to pay by the customer does not. In fact, it may even shrink, which was noted in a MobileCampNYC talk by some smart folks at Air Arts last Saturday. Consumers have been conditioned to expect prices to fall, especially in the area of telecommunication services, even as nodes (and the value of the network) increases. Is the reason that customers don’t want to pay for that additional nodes because the new nodes are less valuable to the customer as the article suggests? Is it a matter of marketing conditioning from other services industries associated with the properties of the economics of scale that prices for services should go down over time?

Although the article was published last year, the valuations for networks will only receive more scrutiny after Facebook’s USD$15 billion valuation, which is about 25 times what News Corp paid for MySpace, which has more than double the users than Facebook. Expect more discussion to follow.

The Apple developer’s kit for the iPhone and the Google phone is getting a lot discussion in the press. They are just two examples of that “innovation” has been getting attention recently. Despite all the discussion on innovation, I don’t feel like there is a standard language or measure to accurately describe what’s going on. Here are some graphs that I’ve been carrying around in my head, which are trying to categorize innovation or at least start to recognize patterns. As a proxy for innovation, I’m using hacks, which I defined broadly, as modifications to a product or system or service, for some unintended use, application, or outcome by the original source. The relationship between hacking and innovation probably deserves its own post, which I’ll try to get to soon.

In the graph, the y axis is roughly the number or frequency of hacks, which doesn’t have a scale, because it’s based on theoretical model. The x axis is time and show how the number of hack change over time. The graph isn’t always upward because hacks can become obsolete or blocked.

Graph 1 Creative Destruction: Schumpeter’s ideas on creative destruction talks about how a disruptive technology or change affects the rate of hacks and innovation can be caused by events. An obvious example is Facebook’s decision to allow third part developers to create applications for its site. Overall, this situation doesn’t depend on moving from a open to a closed system. Sometimes a technical innovation that allows for innovation. For instance, movable type and wordpress blogging software made the web much more hackable by removing the need to know much about html and ftp to start a blog.

Graph 2 Eventual Obsolescence shows how a product or service, which is very hackable, can become less so over time. Many factors can be the cause of this change. Sometimes it is a matter of the product becoming more sophisticated, which makes modification harder for the amateur hacker. For instance, a Ford LTD station wagon from the 1980s was much easier to hack than a 2008 BMW 5-Series 535XI Wagon, which uses more synthetic materials and is loaded with electronics. In this case, automakers didn’t make create more sophisticated specifically to stop hacking. Open system become closed intentionally, as seen in the telephone system which was originally much easier to hack than it is today.

Graph 3 Build-A-Better-Mousetrap is the typical game that closed manufactures or service providers play with hackers. This is often the case for apps to break DRM or download songs off an iPod, where each software upgrade plugs up the hole, or in some cases turn your iPhone into a brick. People are trying to innovation, but their progress faces impediments. This start and stopping isn’t always a bad thing. Spam, besides masking originating email addresses, is essentially a hack of text (and interesting notion within itself,) where malicious email is created by altering text in order to fool spam filters into thinking its contain is legitimate.

Graph 4 Network Effects is a model of an open platform, such as Facebook, after they released their developer’s kits. The idea than an open platform will create value by increasing the users options, which will lead to more users. More users, in turn, will encourage more innovation, or so the ideal case goes. Nokia has an developer’s kit and Apple intends to do the same for phone. However, this example isn’t necessary an ideal as well. Too many apps creates too many choices, which can confuse and ultimately drive away users.

Identifying these patterns and clusters are only the first step. The steps will probably involve identifying outcomes and finally measures (even qualitative ones) to describe what happened. So, there is a lot to do, but this is a start.

Here is a photo I took earlier this year at the then brand new Bangkok International Suvarnabhumi Airport (BKK). I was thinking about the image today, while doing some reading on social network theory. Airports are transportation hubs and feel weird when they are empty, because they are not acting out their function as place of transit. Shininess didn’t help matters at all either.

Some new points have instant connections while others don’t. I’m interested in how new points form and get connected into a network. Some points appear with a social network in place, say a baby born into a large family. Other points have connections which exist in other networks and their entry into a new network gives them instant connections as well. Steven Colbert made 1 million facebook friends in a week, which shows spill over from other networks. This is all obvious, but I’m curious if there are ways to show how different networks interrelated.

I will add more here, but I’m late for dinner.