Task Scheduling Algorithm Using Covariance Matrix Adaptation Evolution Strategy (CMA-ES) in Cloud Computing
سال انتشار: 1396
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 447
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شناسه ملی سند علمی:
JR_JACET-3-3_002
تاریخ نمایه سازی: 18 تیر 1398
چکیده مقاله:
The cloud computing is considered as a computational model which provides the uses requests with resources upon any demand and needs.The need for planning the scheduling of the user s jobs has emerged as an important challenge in the field of cloud computing. It is mainly due to several reasons, including ever-increasing advancements of information technology and an increase of applications and user needs for these applications with high quality, as well as, the popularity of cloud computing among user and rapidly growth of them during recent years. This research presents the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), an evolutionary algorithm in the field of optimization for tasks scheduling in the cloud computing environment. The findings indicate that presented algorithm, led to a reduction in execution time of all tasks, compared to SPT, LPT, and RLPT algorithms.Keywords: Cloud Computing, Task Scheduling, Virtual Machines (VMs), Covariance Matrix Adaptation Evolution Strategy (CMA-ES)
کلیدواژه ها:
Cloud Computing ، Task Scheduling ، Virtual Machines(Vms) ، Convariance Matrix Adaptation Evolution Strategy(CMA-ES)
نویسندگان
Ghazaal Emadi
Science and Research Branch, Islamic Azad University, Tehran, Iran.
Amir Masoud Rahmani
Department of Computer Engineering Science and Research Branch, Islamic Azad University, Tehran, Iran.
Hamed Shahhoseini
Science and Research Branch, Islamic Azad University, Tehran, Iran.