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Lifetime Improvement in Wireless Sensor Networks using Hybrid Differential Evolution and Simulated Annealing (DESA)
Potthuri S, ,
Published in Elsevier BV
Volume: 9
Issue: 4
Pages: 655 - 663
The major concerns in Wireless Sensor Networks (WSN) are energy efficiency as they utilize small sized batteries, which can neither be replaced nor be recharged. Hence, the energy must be optimally utilized in such battery operated networks. One of the traditional approaches to improve the energy efficiency is through clustering. In this paper, a hybrid differential evolution and simulated annealing (DESA) algorithm for clustering and choice of cluster heads is proposed. As cluster heads are usually overloaded with high number of sensor nodes, it tends to rapid death of nodes due to improper election of cluster heads. Hence, this paper aimed at prolonging the network lifetime of the network by preventing earlier death of cluster heads. The proposed DESA reduces the number of dead nodes than Low Energy Adaptive Clustering Hierarchy (LEACH) by 70%, Harmony Search Algorithm (HSA) by 50%, modified HSA by 40% and differential evolution by 60%. © 2016 Faculty of Engineering, Ain Shams University
About the journal
JournalData powered by TypesetAin Shams Engineering Journal
PublisherData powered by TypesetElsevier BV
Open AccessNo