A Cellular Automata Model for Immune Based Search Algorithm

Decentralized peer to peer networks like Gnutella are attractive for certain applications because they require no centralized directories and no precise control over network topology or data placement. The greatest advantage is the robustness provided by them. However, flooding based query algorithms used by the networks produce enormous amount of traffic and substantially slow down the system. Recently flooding is increasingly replaced with more efficient k-random walkers and different variants of such algorithms [6]. In this paper, we develop an efficient search algorithm for p2p networks with the help of a 2-dimensional Cellular Automata 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 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.