Mitigating Hotspot Problem Using Northern Goshawk Optimization Based Energy Aware Multi-Hop Communication for Wireless Sensor Networks  

作　　者：S.Leones Sherwin Vimalraj J.Lydia 

机构地区：[1]Department of Electronics and Communication Engineering,Panimalar Engineering College,Chennai 600123,India [2]Department of Electrical and Electronics Engineering,Easwari Engineering College,Chennai 600089,India

出　　处：《China Communications》2025年第2期283-298,共16页中国通信(英文版)

摘　　要：Wireless Sensor Network(WSN)comprises a set of interconnected,compact,autonomous,and resource-constrained sensor nodes that are wirelessly linked to monitor and gather data from the physical environment.WSNs are commonly used in various applications such as environmental monitoring,surveillance,healthcare,agriculture,and industrial automation.Despite the benefits of WSN,energy efficiency remains a challenging problem that needs to be addressed.Clustering and routing can be considered effective solutions to accomplish energy efficiency in WSNs.Recent studies have reported that metaheuristic algorithms can be applied to optimize cluster formation and routing decisions.This study introduces a new Northern Goshawk Optimization with boosted coati optimization algorithm for cluster-based routing(NGOBCO-CBR)method for WSN.The proposed NGOBCO-CBR method resolves the hot spot problem,uneven load balancing,and energy consumption in WSN.The NGOBCO-CBR technique comprises two major processes such as NGO based clustering and BCO-based routing.In the initial phase,the NGObased clustering method is designed for cluster head(CH)selection and cluster construction using five input variables such as residual energy(RE),node proximity,load balancing,network average energy,and distance to BS(DBS).Besides,the NGOBCO-CBR technique applies the BCO algorithm for the optimum selection of routes to BS.The experimental results of the NGOBCOCBR technique are studied under different scenarios,and the obtained results showcased the improved efficiency of the NGOBCO-CBR technique over recent approaches in terms of different measures.

关 键 词：CLUSTERING energy efficiency metaheuristics multihop communication network lifetime wireless sensor networks 

分 类 号：TN929.5[电子电信—通信与信息系统] TP212.9[电子电信—信息与通信工程]