Optimum K-coverage in Wireless Sensor Network with no Redundant Node by Cellular Learning Automata
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Wireless Sensor Networks have been widely considered as one of the most important technologies for the twenty-first century. Thus, the coverage and energy consumption are the key issues of wireless sensor network research. Some protocols such as SKS and CCA have been developed recently to achieve k-coverage in dense sensor networks along with maximizing network lifetime and removing redundant active nodes. In this paper, we propose a new distributed location unaware algorithm named CLARRKC in order to maintain full k-coverage as long as possible while deactivating all of redundant nodes by Cellular Learning Automata. CLARRKC has considerably low communication and computation complexity and is of degree O(1). It uses load balancing and does not need sensors location information. Simulations show that our work can maintain full k-coverage up to 60% of network lifetime and outperforms other state-of-the-art protocols i.e. SKS and CCA in terms of activated nodes and energy consumption.
KeywordsCellular learning automata Wireless sensor networks K-coverage Redundant node Dense sensor networks
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