Simple search lightens Net load " Researchers from the University of California at Los Angeles have devised a fast search algorithm that uses local rules to find nodes and content in randomly-formed, scale-free networks such as the Internet."
"The researchers' algorithm is based on the bond percolation threshold, or the smallest probability that a message is guaranteed to reach a core sub-network of highly-connected nodes, said Roychowdhury.
As connections randomly percolate through the network at a low rate, only small, isolated islands form. Once the bond percolation threshold is passed, the core of the network becomes connected. The threshold is an abrupt phase transition like the quick transformation of would in that takes place when water boils or freezes.
The algorithm involves three basic steps: content caching, query implantation, and bond percolation, said Roychowdhury.
Content caching happens when a node joins a peer-to-peer network and performs a one-time short random survey, or walk of nearby nodes and adds its content directory to each of these neighboring nodes.
The query implementation step is similar, but happens at the beginning of every query. When a node has a query, it performs a short random walk and passes the query along to each node it encounters.
These random walks are long enough that any given node will almost surely encounter at least one highly-connected node, said Roychowdhury. "So after these two steps one of the high-degree nodes has a copy of a node's directory, and a query is implanted at one of the high-degree nodes.""
"The key step in working out the algorithm was making sure that each query could reach a high-degree node starting from any node in the network. The conceptual breakthrough was the realization that the whole search process could be implemented locally, through messages passed among neighbors only, said Nima Sarshar, a researcher at the University of California at Los Angeles."
For some background see: Linked.
Matter's has a follow up with a link to: Scalable Percolation Search in Power Law Networks .
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