基于 CN-Graph 的移动边缘计算容器优化匹配部署算法

Huanle Rao, Sheng Chen, Yuxuan Du, Xiaobin Xu, Haodong Chen, Gangyong Jia
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摘要

在边缘设备上部署日益多样化的服务正变得越来越普遍。如何将功能异构的服务高效地部署到资源异构的边缘节点上,同时实现卓越的用户体验,是每个边缘系统必须应对的挑战。本文提出了一种基于容器-节点图(CN-Graph)的容器优化匹配部署算法,即基于容器-节点图的边缘库恩-蒙克雷斯算法(EKM),旨在异构环境中优化系统性能。首先,根据功能标签对容器进行分类,然后根据容器和节点之间的关系构建 CN-Graph 模型。最后,容器部署问题被转化为加权双向图最优匹配问题。与主流的容器部署算法Swarm、Kubernetes和最近出现的ECSched-dp算法相比,EKM算法能有效提高容器的平均运行性能,分别达到3.74倍、4.10倍和2.39倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A container optimal matching deployment algorithm based on CN-Graph for mobile edge computing

The deployment of increasingly diverse services on edge devices is becoming increasingly prevalent. Efficiently deploying functionally heterogeneous services to resource heterogeneous edge nodes while achieving superior user experience is a challenge that every edge system must address. In this paper, we propose a container-node graph (CN-Graph)-based container optimal matching deployment algorithm, edge Kuhn-Munkres algorithm (EKM) based on container-node graph, designed for heterogeneous environment to optimize system performance. Initially, containers are categorized by functional labels, followed by construction of a CN-Graph model based on the relationship between containers and nodes. Finally, the container deployment problem is transformed into a weighted bipartite graph optimal matching problem. In comparison with the mainstream container deployment algorithms, Swarm, Kubernetes, and the recently emerged ECSched-dp algorithm, the EKM algorithm demonstrates the ability to effectively enhance the average runtime performance of containers to 3.74 times, 4.10 times, and 2.39 times, respectively.

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