基于带宽预测与自适应压缩的容器迁移方法

doi:10.19678/j.issn.1000-3428.0061758

计算机工程 ›› 2022, Vol. 48 ›› Issue (5): 200-207,214. doi: 10.19678/j.issn.1000-3428.0061758

基于带宽预测与自适应压缩的容器迁移方法

罗成^1,2,3, 崔勇⁴, 林予松^1,2,3

1. 郑州大学软件学院, 郑州 450002;
2. 郑州大学汉威物联网研究院, 郑州 450002;
3. 郑州大学互联网医疗与健康服务河南省协同创新中心, 郑州 450052;
4. 郑州轻工业大学计算机与通信工程学院, 郑州 450002

收稿日期:2021-05-26 修回日期:2021-07-26 发布日期:2021-08-09
作者简介:罗成(1995—),男,硕士研究生,主研方向为边缘计算;崔勇,讲师、博士;林予松,教授、博士。
基金资助:
国家自然科学基金面上项目（81772009）；河南省科技攻关计划（212102210409）；郑州市协同创新重大专项（20XTZX06013，20XTZX05015）。

Container Migration Method Based on Bandwidth Prediction and Adaptive Compression

LUO Cheng^1,2,3, CUI Yong⁴, LIN Yusong^1,2,3

1. School of Software, Zhengzhou University, Zhengzhou 450002, China;
2. Hanwei IoT Institute, Zhengzhou University, Zhengzhou 450002, China;
3. Collaborative Innovation Center of Internet Medical & Healthcare in Henan, Zhengzhou University, Zhengzhou 450052, China;
4. School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China

Received:2021-05-26 Revised:2021-07-26 Published:2021-08-09

摘要/Abstract

摘要： 随着数字化技术的发展与工业自动化应用范围的扩大，在万物互联环境下边缘设备数量快速增长，这些设备产生的数据量激增，导致网络带宽逐渐成为边缘计算的瓶颈。针对移动边缘服务迁移过程中传输数据量过大以及边缘节点网络环境不稳定等问题，结合带宽预测和数据压缩技术，提出一种面向Docker容器的服务迁移方法。通过预测网络带宽动态调整数据压缩算法的压缩速度以及压缩强度，从而充分利用网络带宽和多核处理器的计算能力，最大限度地减少网络传输的数据量以及服务的停机时间。实验结果表明，该方法对网络环境变化具有较强的适应性，能有效平衡数据传输和压缩计算的时间开销，提高服务迁移性能，相比于容器本地服务迁移、基于Docker基础镜像的服务迁移等方法，迁移时间、传输数据量和停机时间至少减少了23.7%、19.4%和17.6%。

关键词: 边缘计算, 服务迁移, 带宽预测, 自适应压缩, Docker容器

Abstract: With the development of digital technology and the expansion of industrial automation applications, the number of edge devices in the Internet of Everything environment is growing rapidly, and the amount of data generated by these devices is increasing exponentially, making network bandwidth a bottleneck for edge computing. To address the large amount of data transmitted during mobile edge service migration and the nonstationary characteristics of edge node network environments, a Docker container-oriented edge service migration method is proposed based on bandwidth prediction and data compression technology. Through bandwidth prediction technology, the compression speed and strength of the data compression algorithm are adjusted dynamically to fully utilize the network bandwidth, and the power of the multicore processor is computed to minimize service downtime and the amount of data transmitted on the network. The experimental results show that this method is more adaptable to changes in the network environment and can effectively balance the time overhead of data transmission and compression calculation, thereby improving the performance of service migration. Compared with Pre-copy, LZ4-ACM, and other migration methods, this method reduces the migration time by at least 23.7%, the amount of data transferred by at least 19.4%, and downtime by at least 17.6%.

Key words: edge computing, service migration, bandwidth prediction, adaptive compression, Docker container

中图分类号:

TP391

罗成, 崔勇, 林予松. 基于带宽预测与自适应压缩的容器迁移方法[J]. 计算机工程, 2022, 48(5): 200-207,214.

LUO Cheng, CUI Yong, LIN Yusong. Container Migration Method Based on Bandwidth Prediction and Adaptive Compression[J]. Computer Engineering, 2022, 48(5): 200-207,214.

https://www.ecice06.com/CN/Y2022/V48/I5/200

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