摘要
针对集群负载动态变化引发容器频繁迁移的问题,提出了一种基于资源预留的容器部署方法。首先,设计了基于马尔可夫链模型的单容器资源需求动态变化描述机制,用于刻画单容器的资源需求情况;其次,基于单容器马尔可夫链模型分析了多容器资源动态变化情况,以刻画容器资源需求态势;随后,基于多容器马尔可夫链提出了面向动态负载的容器部署与资源预留算法;最后,基于容器资源需求特征的分析对所提算法的性能进行了优化。基于国产软硬件环境构建了仿真实验环境,仿真结果表明,在资源冲突率方面,所提方法的性能接近最优的峰值配置策略RP,但所需宿主机数量、容器动态迁移次数明显比其更少;在资源利用率方面,所提方法的宿主机使用数量略多于最优的谷值配置策略RV,但动态迁移次数更少,资源冲突率更低;相较于峰谷配置策略RVP,所提方法在综合性能方面更佳。
Aiming at the problem of frequent migration of containers triggered by dynamic changes of cluster workload,a container deployment method based on resource reservation was proposed.Firstly,a dynamic change description mechanism of single-container resource demand based on Markov chain model was designed to describe the resource demand situation of single container.Secondly,the dynamic change of multi-container resource was analyzed based on the single-container Markov chain model to describe the container resource demand state.Thirdly,a container deployment and resource reservation algorithm for dynamic workload was proposed based on the multi-container Markov chain.Finally,the performance of the proposed algorithm was optimized based on the analysis of container resource demand characteristics.The simulation experimental environment was constructed based on the domestic software and hardware environment,and the simulation results show that in terms of resource conflict rate,the performance of the proposed method has the performance close to the optimal peak allocation strategy named Resource with Peak(RP),but its number of required hosts and container dynamic migration number are significantly less;in terms of resource utilization rate,the proposed method has the number of hosts used slightly more than the optimal valley allocation strategy named Resource with Valley(RV),but has less dynamic migration number and lower resource conflict rate;compared with the peak and valley allocation strategy named Resource with Valley and Peak(RVP),the proposed method has better comprehensive performance.
作者
尹飞
龙玲莉
孔峥
邵涵
李鑫
钱柱中
YIN Fei;LONG Lingli;KONG Zheng;SHAO Han;LI Xin;QIAN Zhuzhong(Jiangsu Frontier Electric Technology Company Limited,Nanjing Jiangsu 211102,China;Department of Computer Science and Technology,Nanjing University,Nanjing Jiangsu 210023,China;College of Computer Science and Technology,Nanjing University of Aeronautics and Astronautics,Nanjing Jiangsu 211106,China)
出处
《计算机应用》
CSCD
北大核心
2021年第6期1581-1588,共8页
journal of Computer Applications
基金
国家自然科学基金资助项目(61802182)。
关键词
集群
容器
动态负载
整合与迁移
马尔可夫链
cluster
docker
dynamic workload
consolidation and migration
Markov chain
