Abstract
With the rise of 5G/6G and cloud computing, cluster management has become increasingly popular. Elastic cluster resources allow cloud clients to dynamically scale their resource requirements over time. Existing researches of cluster schedulers focus on improving resource scheduling speed, increasing cluster utilization, compacting the number of active physical machines (PMs) and time satisfaction function (TSF) within a cluster. The TSF is applied as a time to measure the parallel-VM scheduling problem. However, completing execution time (makespan) of task requests is often neglected, which results in inaccurate scheduling and unreasonable total cost computation. The total cost involves PM cost, migrate cost, and balance cost. To solve the problem of inaccurate scheduling of task requests and total cost billing in cluster management, in this paper, we propose an innovative heuristic algorithm, namely, multi-objective two-stage variable neighborhood searching (MO_STVNS), which aims at minimizing total cost while also considering TSF for active PMs. Moreover, we design a Multi-Objective FreeVM (MO-FreeVM) scheduler based on resource prediction, which incorporates a variety of algorithms to work in collaboration to provide near-optimal resource management for cluster. We evaluate MO_STVNS in different real traces and measure it through extensive experiments. The experimental results show that compared with state-of-art methods, the average total cost and average TSF of MO_STVNS are reduced by 33.75% and 60.67% respectively.
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Funding
The work was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 62172054, the Key Project of Beijing Natural Science Foundation under M21030, the NSFC under Grant 62072047, and the National Key R&D Program of China under Grant 2019YFB1802603.
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Methodology, Shiyan Zhang; Writing-original draft preparation, Shiyan Zhang; Writing review and editing, Shiyan Zhang, Ran Wang; Funding acquisition, Yuchao Zhang. All authors have read and agreed to the published version of the manuscript.
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Zhang, S., Zhang, Y., Wang, R. et al. MO-FreeVM: multi-objective server release algorithm for cluster resource management. Cluster Comput 26, 1011–1034 (2023). https://doi.org/10.1007/s10586-022-03663-7
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DOI: https://doi.org/10.1007/s10586-022-03663-7