Authors:
Mohammed Kayed
1
;
Ahmed Anter
1
and
Ahmed Hassan
2
Affiliations:
1
Faculty of Computers and Information, Beni-Suef University, Beni-suef, Egypt, 62511, Egypt
;
2
Faculty of Science, Beni-Suef University, Beni-suef, Egypt, 62511, Egypt
Keyword(s):
Wireless Sensor Networks, Cluster Head, Wireless Power Transfer, Particle Swarm Optimization
Abstract:
Clustering sensor nodes in power-constrained Wireless Sensor Network (WSN) is an efficient step to enhance energy efficiency and extend the network lifetime. Clustering gives many advantages (e.g., data aggregation and less number of transmissions) that greatly reduces the energy consumption of the WSN. A Cluster Head (CH) node is selected for each cluster to receive data from the cluster’s nodes, aggregate them, and finally transmit these data to a Base Station (BS). However, the overhead on the CH nodes is still a problem for the network lifetime, which causes premature death for those overloaded nodes. Energy harvesting is one of the most energy optimization techniques that make the WSN rechargeable and so extends the lifetime of the network. Traditional techniques such as solar and wind harvesting are not reliable because they are neither constant nor always available. Another type of energy harvesting is the Wireless Power Transfer (WPT) approach in which a node enables to trans
fer energy to other nodes. According to the energy consumption theory in WSN, about 90% of energy is left unused after the premature death of overloaded nodes. If this big surplus of energy is used to recharge the overloaded nodes, it will greatly extend the lifetime of the WSN. So, in this paper, we use the WPT technology and the multi-objective Particle Swarm Optimization (PSO) to extend the network lifetime. The target of our proposed approach is to minimize the amount of this surplus of energy. All nodes in the WSN could transfer energy to the CH nodes to distribute the overall load. At the same time, the optimal amount of energy, transferred by each node, must also be convenient to its residual energy. Therefore, this paper tries to eliminate the overhead on the CH nodes and therefore extend the lifetime of the clustered WSN. Our simulation results show an encouraging result to extend the lifetime of the WSNs as compared with the common Leach algorithm.
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