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Discrete Interior Search Algorithm for Multi-resource Fair Allocation in Heterogeneous Cloud Computing Systems
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  • 关键词:Dominant resource fairness ; Interior search algorithm ; Multi ; resource fair allocation ; Heterogeneous cloud
  • 刊名:Lecture Notes in Computer Science
  • 出版年:2016
  • 出版时间:2016
  • 年:2016
  • 卷:9771
  • 期:1
  • 页码:615-626
  • 全文大小:2,326 KB
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  • 作者单位:Xi Liu (16)
    Xiaolu Zhang (16)
    Weidong Li (16)
    Xuejie Zhang (16)

    16. School of Information Science and Engineering, Yunnan University, No. 2, North Cuihu Road, Wuhua District, Kunmming, 650091, Yunnan, People’s Republic of China
  • 丛书名:Intelligent Computing Theories and Application
  • ISBN:978-3-319-42291-6
  • 刊物类别:Computer Science
  • 刊物主题:Artificial Intelligence and Robotics
    Computer Communication Networks
    Software Engineering
    Data Encryption
    Database Management
    Computation by Abstract Devices
    Algorithm Analysis and Problem Complexity
  • 出版者:Springer Berlin / Heidelberg
  • ISSN:1611-3349
  • 卷排序:9771
文摘
The mechanism of resource allocation for cloud computing not only affects the users’ fairness, but also has a significant impact on resource utilization. Most current resource allocation models did not take into account the indivisible demands, the heterogeneity servers, and the situations multi-server. Dominant resource fairness allocation in heterogeneous systems (DRFH) is a fair and efficient resource allocation mechanism. But solving the DRFH problem is NP-hard. There are significant gaps between solutions obtained by existing heuristic algorithms and optimal solutions. They cannot effectively use server resources, resulting in a waste of resources of servers. In this paper, we propose a novel discrete interior search algorithm (DISA) to solve indivisible demands in heterogeneous servers, with a specific repair operator and task-fit value. Experimental results demonstrate that DISA can well adapt to dynamic changes in user resource request type, obtain the near-optimal solutions, maximize the value of minimum global dominant share and resource utilization.

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