Technology Review
How a 1960s sociology experiment could hold the key to better Internet routing.
Just like an old-fashioned piece of mail, data traveling over the Internet normally follows a predictable path. As the Internet continues to grow, however, experts have begun to worry that current routing protocols will be unable to cope with increased congestion. And so, as researchers search for new solutions, some are taking inspiration from a famous social experiment that called on people to deliver mail using only a network of friends.
For many years, Internet routers have used a standard known as the border gateway protocol (BGP) to map out the path that data takes. BGP requires each router to store a list of network addresses, known as a routing table, which tells it where to forward packets of information (based on a complete picture of that network). But as the number of Internet-connected machines increases, routing tables grow longer and need to receive updates more frequently, potentially slowing some traffic to a crawl. A major sticking point for the BGP protocol is that every time part of the network changes, every router must process an update.
This is where the work of sociologist Stanley Milgram could help out. Milgram carried out experiments in the 1960s that helped make famous the idea of "six degrees of separation." Milgram gave volunteers the task of forwarding a letter to a stranger by sending it to friends or acquaintances that might be one step closer to the target. Milgram measured how many hops there were between the sender and the end recipient, and found it to be, on average, 5.2. (The term six degrees of separation was coined later by playwright John Guare.)
In 2000, inspired by Milgram's work, Jon Kleinberg, a professor of computer science at Cornell University, in New York, created a mathematical model for routing information across any kind of network. Kleinberg says that he drew from the fact that Milgram "demonstrated not just that short paths were present in large social networks, but that people--operating without a global view of the network--could efficiently find them."
Now, research from Marián Boguñá at the University of Barcelona and colleagues, suggests that the approach could indeed by applied to real-world networks, including the Internet's routing system. In work published recently in Nature Physics, Boguñá and his colleagues argue that the work of Kleinberg and others can be applied to real-world networks and, specifically, could be used to design a protocol that allows routers to keep track of less information about a network, thereby reducing congestion.
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Hybrid approach will be best, 2/3
Hybrid approach will be best, 2/3 look up 1/3 dynamic "pass along to a friend" approach...
As 1/3 finds more efficient low volume routes (or low congested routes if these routes handle less traffic) These can be swapped for over taxed main pathways to free up congestion on those routes only.
So lets say the 1/2 of the total or 3/6 would be static and when changed would need a system wide look up table update only thus rarely updated. the other 1/6 of the 4/6 of the static 2/3 would be suto-static and only be upated on a sub-set of total look up tables. The remaining 1/3 would be true dynamic with a constant sorting of free bandwitdth that can be swapped up to the top half of the 1/3 (1/6) with the suto-static 1/6 as needed.
Also the static and suto-static would be sorted per congestion to optimize at look up update time.
with most congested being sorted into suto-static prioritization,to offload traffic to dynamic maximum free bandwith sorted prioritzation candidates.
Your fractions may vary...
:)
Peace out
Wouldn't it be interesting if switched systems turned out to be a better solution than routing? And the Bell system's century-old methods were the most efficient?!
The flip side of the small world phenomenon is non-localisation. When events at the very edge of the network cause changes at the core of the network. Particle physics provides plenty of evidence.
The six degree paths are two-way channels and so design must proceed with caution to avoid becoming a victim of unintended consequences.
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phoenix
172 Comments
information overload
All arguments of a particular function are defined as a set of parameters and as such fall into a definite set of categories each displaying a different set of characteristics. The only problem with using probability factors is that you have to distinguish between free or bound variables. Although the probability framework may apply, attention cannot shift from estimating the variables from observed data to testing hypothesis about them. While classical estimations consider parameters as fixed but unknown, Bayesian models constitute random variables with their own distribution. In other words trying to assign an arbitrary set of constants to find the hidden metrics of a particular function is like herding cats. While it is theoretically possible, the eventual outcome is pretty much a forgone conclusion.
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