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Designing a Hybrid Clustering Routing Algorithm based on Cellular Learning Automata for Optimizing Lifetime of Wireless Sensor Networks

One of the most important factors in wireless sensor networks is energy consumption, hence the lifetime of these networks are strongly depending on remaining energy in the nodes. According to sensors placement farness and wireless communication between them, it is necessary to optimally consume the energy in these networks. In this study a hybrid approach is proposed by mixing two existing protocols, namely flat multi-hop routing and hierarchical multi-hop routing. Also by using Cellular Learning Automata (CLA) as clustering technique, the energy in the network will be managed and finally the lifetime of nodes will be increased. Mathematical simulation and analysis show a good performance of clustered hybrid model for energy saving that in compare with multi hop routing algorithm and hierarchical routing in non-clustered and clustered conditions, the lifetime increasing are %10.39, %27.36 and %5.57, %23.83 respectively.