A packet routing strategy using neural networks on scale-free networks

Yuki Naganuma and Akito Igarashi

Physica A: Statistical Mechanics and its Applications, 2010, vol. 389, issue 3, 623-628

Abstract: We propose a dynamic packet routing strategy by using neural networks on scale-free networks. In this strategy, in order to determine the nodes to which the packets should be transmitted, we use path lengths to the destinations of the packets, and adjust the connection weights of the neural networks attached to the nodes from local information and the path lengths. The performances of this strategy on scale-free networks which have the same degree distribution and different degree correlations are compared to one another. Our numerical simulations confirm that this routing strategy is more effective than the shortest path based strategy on scale-free networks with any degree correlations and that the performance of our strategy on assortative scale-free networks is better than that on disassortative and uncorrelated scale-free networks.

Keywords: Neural network; Computer network; Packet routing; Complex network; Scale-free network (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:389:y:2010:i:3:p:623-628

DOI: 10.1016/j.physa.2009.09.048

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