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发表刊物：IEEE Transactions on Automation Science and Engineering
刊物所在地：美国
关键字：Data centers, energy optimization, green clouds, multiobjective evolutionary algorithm, task schedul
摘要：The significant growth in the number and types of tasks of heterogeneous applications in green cloud data centers (GCDCs) dramatically increases their providers’ revenue from users as well as energy consumption. It is a big challenge to maximize such revenue, while minimizing energy cost in a market where prices of electricity, availability of renewable power generation, and behind-the-meter renewable generation contract models differ among the geographical sites of the GCDCs. A multiobjective optimization method that investigates such spatial differences in the GCDCs is for the first time pro
论文类型：基础研究
论文编号：DOI: 10.1109/TASE.2020.2971512
一级学科：计算机科学与技术
文献类型：期刊
卷号：18
期号：2
页面范围：817-830
ISSN号：1545-5955
是否译文：否
CN号：null
发表时间：2021-04-01
收录刊物：SCI
发布期刊链接：https://ieeexplore-ieee-org-s.vpn.buaa.edu.cn:8118/document/9011590