Enhanced Metaheuristics-Based Clustering Scheme for Wireless Multimedia Sensor Networks
作者机构:Department of Computer Science and EngineeringVardhaman College of Engineering(Autonomous)HyderabadTelangana501218India Department of Computer ScienceCollege of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Electrical EngineeringCollege of EngineeringJouf UniversitySaudi Arabia Department of Computer Science and EngineeringVignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Computer Science and EngineeringSejong UniversitySeoul05006Korea Department of Software ConvergenceDaegu Catholic UniversityGyeongsan38430Korea
出 版 物:《Computers, Materials & Continua》 (计算机、材料和连续体(英文))
年 卷 期:2022年第73卷第11期
页 面:4179-4192页
核心收录:
学科分类:08[工学] 0805[工学-材料科学与工程(可授工学、理学学位)] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 081102[工学-检测技术与自动化装置] 0812[工学-计算机科学与技术(可授工学、理学学位)]
基 金:Ulsan City, (22AS1600) Electronics and Telecommunications Research Institute, ETRI
主 题:Wireless multimedia sensor networks clustering spider monkey optimization algorithm energy efficiency metaheuristics quantum computing
摘 要:Traditional Wireless Sensor Networks(WSNs)comprise of costeffective sensors that can send physical parameters of the target environment to an intended *** the evolution of technology,multimedia sensor nodes have become the hot research topic since it can continue gathering multimedia content and scalar from the target *** existence of multimedia sensors,integrated with effective signal processing and multimedia source coding approaches,has led to the increased application of Wireless Multimedia Sensor Network(WMSN).This sort of network has the potential to capture,transmit,and receive multimedia *** energy is a major source in WMSN,novel clustering approaches are essential to deal with adaptive topologies of WMSN and prolonged network *** this motivation,the current study develops an Enhanced Spider Monkey Optimization-based Energy-Aware Clustering Scheme(ESMO-EACS)for *** proposed ESMO-EACS model derives ESMO algorithm by incorporating the concepts of SMO algorithm and quantum *** proposed ESMO-EACS model involves the design of fitness functions using distinct input parameters for effective construction of clusters.A comprehensive experimental analysis was conducted to validate the effectiveness of the proposed ESMO-EACS technique in terms of different performance *** simulation outcome established the superiority of the proposed ESMO-EACS technique to other methods under various measures.