[2305.13732] Task Containerization and Container Placement Optimization for MEC: A Joint Communication and Computing Perspective
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Computer Science > Distributed, Parallel, and Cluster Computing

arXiv:2305.13732 (cs)
[Submitted on 23 May 2023]

Title:Task Containerization and Container Placement Optimization for MEC: A Joint Communication and Computing Perspective

Authors:Ao Liu, Shaoshi Yang, Jingsheng Tan, Zongze Liang, Jiasen Sun, Tao Wen, Hongyan Yan
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Abstract:Containers are used by an increasing number of Internet service providers to deploy their applications in multi-access edge computing (MEC) systems. Although container-based virtualization technologies significantly increase application availability, they may suffer expensive communication overhead and resource use imbalances. However, so far there has been a scarcity of studies to conquer these difficulties. In this paper, we design a workflow-based mathematical model for applications built upon interdependent multitasking composition, formulate a multi-objective combinatorial optimization problem composed of two subproblems -- graph partitioning and multi-choice vector bin packing, and propose several joint task-containerization-and-container-placement methods to reduce communication overhead and balance multi-type computing resource utilization. The performance superiority of the proposed algorithms is demonstrated by comparison with the state-of-the-art task and container scheduling schemes.
Comments: 11 pages, 8 figures
Subjects: Distributed, Parallel, and Cluster Computing (cs.DC); Networking and Internet Architecture (cs.NI)
Cite as: arXiv:2305.13732 [cs.DC]
  (or arXiv:2305.13732v1 [cs.DC] for this version)
  https://doi.org/10.48550/arXiv.2305.13732
Journal reference: Processes 2023, 11(5), pp. 1-19, article number: 1560
Related DOI: https://doi.org/10.3390/pr11051560

Submission history

From: Ao Liu [view email]
[v1] Tue, 23 May 2023 06:38:07 UTC (192 KB)
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