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作 者:R.Rengaraj K.Latha
机构地区:[1]Department of Information Technology,Saranathan College of Engineering,Tiruchirapalli,620012,Tamilnadu,India [2]Department of Computer Science and Engineering,Anna University(BIT Campus),Trichy,620024,Tamilnadu,India
出 处:《Intelligent Automation & Soft Computing》2023年第2期1923-1937,共15页智能自动化与软计算(英文)
摘 要:In cloud computing(CC),resources are allocated and offered to the cli-ents transparently in an on-demand way.Failures can happen in CC environment and the cloud resources are adaptable tofluctuations in the performance delivery.Task execution failure becomes common in the CC environment.Therefore,fault-tolerant scheduling techniques in CC environment are essential for handling performance differences,resourcefluxes,and failures.Recently,several intelli-gent scheduling approaches have been developed for scheduling tasks in CC with no consideration of fault tolerant characteristics.With this motivation,this study focuses on the design of Gorilla Troops Optimizer Based Fault Tolerant Aware Scheduling Scheme(GTO-FTASS)in CC environment.The proposed GTO-FTASS model aims to schedule the tasks and allocate resources by considering fault tolerance into account.The GTO-FTASS algorithm is based on the social intelligence nature of gorilla troops.Besides,the GTO-FTASS model derives afitness function involving two parameters such as expected time of completion(ETC)and failure probability of executing a task.In addition,the presented fault detector can trace the failed tasks or VMs and then schedule heal submodule in sequence with a remedial or retrieval scheduling model.The experimental vali-dation of the GTO-FTASS model has been performed and the results are inspected under several aspects.Extensive comparative analysis reported the better outcomes of the GTO-FTASS model over the recent approaches.
关 键 词:Cloud computing gorilla troops optimizer task scheduling fault tolerant task completion time failure probability
分 类 号:TP13[自动化与计算机技术—控制理论与控制工程]
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