Abstract
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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Acknowledgement
The work is supported in part by the National Natural Science Foundation of China [No. 61170222, 11301466, 11361048], and the Natural Science Foundation of Yunnan Province of China [No. 2014FB114].
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Liu, X., Zhang, X., Li, W., Zhang, X. (2016). Discrete Interior Search Algorithm for Multi-resource Fair Allocation in Heterogeneous Cloud Computing Systems. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Application. ICIC 2016. Lecture Notes in Computer Science(), vol 9771. Springer, Cham. https://doi.org/10.1007/978-3-319-42291-6_61
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DOI: https://doi.org/10.1007/978-3-319-42291-6_61
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