Abstract
Decentralized peer to peer (p2p) networks like Gnutella are so successful because they are robust and require no centralized directories and no precise control over network topology. In this paper, we develop an efficient search algorithm for p2p networks with the help of a 2-dimensional Cellular Automaton (CA) model. The rules followed by each individual cell of the CA are inspired by concepts of natural immune systems whereby the query message packets in the network are spread through opportunistic proliferation. Through a series of experiments, we compare proliferation with different variants of random walk algorithms. The detailed experimental results show message packets undergoing proliferation, spread much faster in the network and consequently produce better search output in p2p networks. Moreover, experimental results show that proliferation rules are extremely scalable and their performance is largely insensitive to the change in dimension of the CA grid.
This work was partially supported by the Future & Emerging Technologies unit of the European Commission through Project BISON (IST-2001-38923).
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Ganguly, N., Deutsch, A. (2004). A Cellular Automaton Model for an Immune-Derived Search Algorithm. In: Sloot, P.M.A., Chopard, B., Hoekstra, A.G. (eds) Cellular Automata. ACRI 2004. Lecture Notes in Computer Science, vol 3305. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30479-1_7
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DOI: https://doi.org/10.1007/978-3-540-30479-1_7
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