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tuesday :: february 4, 2003
   
 
uniting with only a few random links: small-world networking in simulations

Researchers searching for information about highly complex systems, such as the spread of diseases, the rise and fall of financial markets, or cell-phone communication networks, benefit from large-scale networked computer simulation. These simulations are frequently implemented using large networks of computers that break down the problem into many parts. Tackling weighty problems, bit by byte, allows the simulation process to run faster - sometimes.

The problem comes when the computers have to compare notes, says Gyorgy Korniss, from Rensselaer Polytechnic Institute. Korniss' solution is to use 'small-world' networking - which links a computer to its nearest neighbor, and also a few other random computers in the group.

"Our results indicate that only a few random links are necessary for each computer to know how the network as a whole is behaving." Korniss adds. "Many of us know the concept of six degrees of separation in which any one person is only a few acquaintances away from anyone else. The same idea can be applied to complex problem-solving network systems for more effective large-scale model simulations."

Mathematicians Duncan Watts and Steve Strogatz at Cornell University were the first to formulate the significance of small-world networks in natural, artificial, and social systems in 1998. >from *Uniting With Only a Few Random Links: Findings Reported in This Week's Science*, january 30, 2003

related context
>
genes, neurons, internet: organizing principles of networks. november 11, 2002
> think networks: the new science of networks. june 6, 2002
> electronic small world project: how e-mail connects people worldwide. november 29, 2001
> Kevin Bacon shows the way to a much smaller world than we thought, Cornell mathematicians find. "There's a unifying mechanism in nature that makes things small. The harder we look at the world around us, the more we see networks. The traditional approximations of networks -everything is completely ordered or completely random-, cannot in general predict the kinds of properties that we see in small-world networks." june 4, 1998

imago
>
dream networks

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