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Received:August 15, 2022 Revised:September 15, 2022
Received:August 15, 2022 Revised:September 15, 2022
中文摘要: 容器虚拟化技术由于轻量级的特性逐渐在云计算中崭露头角. 容器热迁移是许多云管理能力的基础, 其在最短的宕机时间内, 将运行中的容器完整地迁移到另一个物理节点上继续运行. 性能是容器热迁移研究的重点, 但通过对现有容器热迁移系统的详细分析, 本文发现其中仍然存在着一些影响性能的问题, 包括转储并行度低、预拷贝策略不收敛以及根文件系统与运行状态迁移并行度低等. 针对这些问题, 本文分别提出和设计了资源感知的并行转储机制、基于后拷贝策略的运行状态迁移和基于多优先级的传输调度并行算法等优化策略和算法, 并基于Docker实现了一个高性能容器热迁移系统Dmigrate. 实验结果表明Dmigrate相比于目前最新的研究, 平均可有效减少17.05%的宕机时间, 总迁移时间平均减少24.33%.
Abstract:Container virtualization is emerging in cloud computing due to its lightweight feature. Container live migration is the basis for many cloud management capabilities, which migrates a running container to another physical node with minimal downtime. Performance is the focus of container live migration research, but through a detailed analysis of existing container live migration systems, this study finds that there are still some problems affecting the performance, including low parallelism of dump, non-convergence of pre-copy policy, and low parallelism of root file system and running state migration. To solve these problems, this study proposes and designs three optimization strategies or algorithms including the resource awareness-based parallel dump mechanism, post-copy policy-based running state migration, and multi-priority-based parallel transfer scheduling algorithm. In addition, the paper realizes a high-performance container live migration system, namely, Dmigrate, based on Docker. Experimental results show that compared with the latest research, Dmigrate can effectively reduce downtime by 17.05%, and the total migration time is decreased by 24.33% on average.
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基金项目:
Author Name | Affiliation | |
WANG Zhi-Hui | Software School, Fudan University, Shanghai 200433, China | 19212010028@fudan.edu.cn |
ZHOU Zhong-Jun | Software School, Fudan University, Shanghai 200433, China |
Author Name | Affiliation | |
WANG Zhi-Hui | Software School, Fudan University, Shanghai 200433, China | 19212010028@fudan.edu.cn |
ZHOU Zhong-Jun | Software School, Fudan University, Shanghai 200433, China |
引用文本:
王智慧,周忠君.容器热迁移优化技术研究.计算机系统应用,2023,32(4):86-93
WANG Zhi-Hui,ZHOU Zhong-Jun.Research on Optimization Technology for Container Live Migration.COMPUTER SYSTEMS APPLICATIONS,2023,32(4):86-93
王智慧,周忠君.容器热迁移优化技术研究.计算机系统应用,2023,32(4):86-93
WANG Zhi-Hui,ZHOU Zhong-Jun.Research on Optimization Technology for Container Live Migration.COMPUTER SYSTEMS APPLICATIONS,2023,32(4):86-93