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Metaheuristic Secure Clustering Scheme for Energy Harvesting Wireless Sensor Networks
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作者 s.nithya roopa P.Anandababu +1 位作者 Sibi Amaran Rajesh Verma 《Computer Systems Science & Engineering》 SCIE EI 2023年第4期497-512,共16页
Recently,energy harvesting wireless sensor networks(EHWSN)have increased significant attention among research communities.By harvesting energy from the neighboring environment,the sensors in EHWSN resolve the energy c... Recently,energy harvesting wireless sensor networks(EHWSN)have increased significant attention among research communities.By harvesting energy from the neighboring environment,the sensors in EHWSN resolve the energy constraint problem and offers lengthened network lifetime.Clustering is one of the proficient ways for accomplishing even improved lifetime in EHWSN.The clustering process intends to appropriately elect the cluster heads(CHs)and construct clusters.Though several models are available in the literature,it is still needed to accomplish energy efficiency and security in EHWSN.In this view,this study develops a novel Chaotic Rider Optimization Based Clustering Protocol for Secure Energy Harvesting Wireless Sensor Networks(CROC-SEHWSN)model.The presented CROC-SEHWSN model aims to accomplish energy efficiency by clustering the node in EHWSN.The CROC-SEHWSN model is based on the integration of chaotic concepts with traditional rider optimization(RO)algorithm.Besides,the CROC-SEHWSN model derives a fitness function(FF)involving seven distinct parameters connected to WSN.To accomplish security,trust factor and link quality metrics are considered in the FF.The design of RO algorithm for secure clustering process shows the novelty of the work.In order to demonstrate the enhanced performance of the CROC-SEHWSN approach,a wide range of simulations are carried out and the outcomes are inspected in distinct aspects.The experimental outcome demonstrated the superior performance of the CROC-SEHWSN technique on the recent approaches with maximum network lifetime of 387.40 and 393.30 s under two scenarios. 展开更多
关键词 CLUSTERING wireless sensor networks network lifetime energy efficiency metaheuristics energy harvesting rider optimization
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