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Task Scheduling Optimization in Cloud Computing by Rao Algorithm

Computers, materials & Continua 2022年第9期72卷 4339-4356页

作者： A.Younes m.khelnahary monagi H.Alkinani Hamdy H.El-Sayed Faculty of Computers and Information Department of Computer ScienceSohag UniversitySohag82524Egypt Department of Computer Science and Artificial Intelligence College of Computer Science and EngineeringUniversity of JeddahJeddah21959Saudi Arabia

Cloud computing is currently dominated within the space of highperformance distributed computing and it provides resource polling and ondemand services through the ***,task scheduling problem becomes a very important analysis space within the field of a cloud computing environment as a result of user’s services demand modification *** main purpose of task scheduling is to assign tasks to available processors to produce minimum schedule length without violating precedence *** heterogeneous multiprocessor systems,task assignments and schedules have a significant impact on system *** the heuristic-based task scheduling algorithm,the different processes will lead to a different task execution time(makespan)on a heterogeneous computing ***,a good scheduling algorithm should be able to set precedence efficiently for every subtask depending on the resources required to reduce(makespan).In this paper,we propose a new efficient task scheduling algorithm in cloud computing systems based on RAO algorithm to solve an important task and schedule a heterogeneous multiple processing *** basic idea of this process is to exploit the advantages of heuristic-based algorithms to reduce space search and time to get the best *** evaluate our algorithm’s performance by applying it to three examples with a different number of tasks and *** experimental results show that the proposed approach significantly succeeded in finding the optimal solutions than others in terms of the time of task implementation.

关键词： Heterogeneous processors RAO algorithm heuristic algorithms task scheduling multiprocessing cloud computing

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