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An intelligent scheduling algorithm for resource management of cloud platform

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成果类型:
期刊论文
作者:
Jin, Huixia;Fu, Yuanyuan;Yang, Gelan;Zhu, Xiaoning*
通讯作者:
Zhu, Xiaoning
作者机构:
[Fu, Yuanyuan; Jin, Huixia; Yang, Gelan] Hunan City Univ, Dept Informat Sci & Engn, Yiyang, Hunan, Peoples R China.
[Zhu, Xiaoning] Beijing Univ Posts & Telecommun, Sch Cyberspace Secur, Beijing, Peoples R China.
通讯机构:
[Zhu, Xiaoning] B
Beijing Univ Posts & Telecommun, Sch Cyberspace Secur, Beijing, Peoples R China.
语种:
英文
关键词:
Cloud computing;Deep learning;Distributed computer systems;Learning algorithms;Machine learning;Multitasking;Network security;Reinforcement learning;Scheduling;Virtual machine;Cloud computing technologies;Cloud environments;Intelligent scheduling algorithms;Resource management;Scheduling knowledge;Scheduling policies;Task-scheduling;Task-scheduling algorithms;Scheduling algorithms
期刊:
Multimedia Tools and Applications
ISSN:
1380-7501
年:
2020
卷:
79
期:
7-8
页码:
5335-5353
基金类别:
The authors would like to thank the reviewers for their helpful advices. The National Science and Technology Major Project (Grant No. 2017YFB0803001), Project supported by the Natural Science Foundation of Hunan Province,China(Grant No.2018JJ2023), Scientific Research Fund of Hunan Provincial Education Department(Grant no.17C0295) are gratefully acknowledged.
机构署名:
本校为第一机构
院系归属:
信息与电子工程学院
摘要:
Cloud-computing technologies and their application are becoming increasingly popular, which improves both enterprises’ and individuals’ working efficiency while at the same time greatly reducing users’ cost. Besides, the scale of cloud platform and its application are rapidly expanding. Yet it’s a challenging task to effectively utilize resource and guarantee quality of services to users. The quality of cloud task scheduling algorithm plays a key role in it. For one thing, traditional rule-based scheduling algorithms like FCFS and priority-...

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