Oppositional Red Fox Optimization Based Task Scheduling Scheme for Cloud Environment

作     者：B.Chellapraba D.Manohari K.Periyakaruppan M.S.Kavitha 

作者机构：Department of Information TechnologyKarpagam Institute of TechnologyCoimbatore641032TamilnaduIndia Department of Computer Science and EngineeringSt.Joseph’s Institute of TechnologyChennai600119India Department of Computer Science&EngineeringSNS College of EngineeringCoimbatore641107India Department of Computer Science&EngineeringSNS College of TechnologyCoimbatore641035India 

出 版 物：《Computer Systems Science & Engineering》 (计算机系统科学与工程（英文）)

年 卷 期：2023年第45卷第4期

页      面：483-495页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 081001[工学-通信与信息系统] 

主　　题：Metaheuristics task scheduling cloud computing internet of things makespan red fox optimizer 

摘      要：Owing to massive technological developments in Internet of Things(IoT)and cloud environment,cloud computing(CC)offers a highly flexible heterogeneous resource pool over the network,and clients could exploit various resources on *** IoT-enabled models are restricted to resources and require crisp response,minimum latency,and maximum bandwidth,which are outside the *** was handled as a resource-rich solution to aforementioned *** high delay reduces the performance of the IoT enabled cloud platform,efficient utilization of task scheduling(TS)reduces the energy usage of the cloud infrastructure and increases the income of service provider via minimizing processing time of user ***,this article concentration on the design of an oppositional red fox optimization based task scheduling scheme(ORFOTSS)for IoT enabled cloud *** presented ORFO-TSS model resolves the problem of allocating resources from the IoT based cloud *** achieves the makespan by performing optimum TS procedures with various aspects of incoming *** designing of ORFO-TSS method includes the idea of oppositional based learning(OBL)as to traditional RFO approach in enhancing their efficiency.A wide-ranging experimental analysis was applied on the CloudSim *** experimental outcome highlighted the efficacy of the ORFO-TSS technique over existing approaches.