A Genetic Algorithm for Source Election in Cooperative Clusters Implementing Network Coding

Abstract

Reference scenarios of the present research are clusters of cooperating wireless nodes, implementing random linear network coding to enhance the throughput performance of file downloading and information spreading services. In particular, a sub-set of cluster nodes will access, through their cellular link, parts of a file to be exchanged among all cluster members. The paper focus is on the "source election" issue. The novelty of the research lies in the main problem constraints, which make it far different from (and more exacting than) traditional cluster head election problems: the source number can cover the whole range of nodes and all the nodes must be considered data destinations. We propose a source election algorithm, only based on the knowledge of the number of nodes, which is fast in converging to either the optimal or, alternatively, a satisfactory sub-optimal solution. In so doing, we exploit a performing genetic algorithm. Its observed behaviour makes us confident that the followed approach can be the winning one in conditions of null/limited awareness of node position and type of relevant available cellular links.