Docker,as a mainstream container solution,adopts the Copy-on-Write(CoW)mechanism in its storage drivers.This mechanism satisfies the need of different containers to share the same image.However,when a single container...Docker,as a mainstream container solution,adopts the Copy-on-Write(CoW)mechanism in its storage drivers.This mechanism satisfies the need of different containers to share the same image.However,when a single container performs operations such as modification of an image file,a duplicate is created in the upper readwrite layer,which contributes to the runtime overhead.When the accessed image file is fairly large,this additional overhead becomes non-negligible.Here we present the concept of Dynamic Prefetching Strategy Optimization(DPSO),which optimizes the Co W mechanism for a Docker container on the basis of the dynamic prefetching strategy.At the beginning of the container life cycle,DPSO pre-copies up the image files that are most likely to be copied up later to eliminate the overhead caused by performing this operation during application runtime.The experimental results show that DPSO has an average prefetch accuracy of greater than 78%in complex scenarios and could effectively eliminate the overhead caused by the CoW mechanism.展开更多
针对大规模虚拟机环境下软件的按需部署,提出了一种基于预取的按需软件部署优化机制,能够降低用户端虚拟机的启动延迟以及为用户提供更好的虚拟机本地运行性能.基于用户使用软件的行为特点以及虚拟磁盘映像的细粒度分割,预取机制在后台...针对大规模虚拟机环境下软件的按需部署,提出了一种基于预取的按需软件部署优化机制,能够降低用户端虚拟机的启动延迟以及为用户提供更好的虚拟机本地运行性能.基于用户使用软件的行为特点以及虚拟磁盘映像的细粒度分割,预取机制在后台对服务器端存储的虚拟磁盘映像进行预取,通过一种基于访问频率和优先级的预取目标识别算法AFPTR(access frequency and priority-based prefetch target recognition)和一种预取量动态调节机制,将预取集中在用户使用的少数小尺寸的虚拟磁盘映像上,并在预取过程中对预取量进行动态自适应地调节,以提高虚拟磁盘访问的本地命中率,进而提高用户端虚拟机的运行性能.基于QEMU虚拟机和Linux平台,实现了基于预取的按需软件部署原型系统.实验结果表明,预取机制能够有效地降低虚拟机的启动延迟,并能提高虚拟机的本地运行性能,支持虚拟机环境下按需、快速的软件部署.展开更多
基金supported by the National Key Research and Development Program of China(No.2018YFB1003203)the National Natural Science Foundation of China(Nos.61772218 and 61433019)+1 种基金the Outstanding Youth Foundation of Hubei Province(No.2016CFA032)the Chinese Universities Scientific Fund(No.2019kfyRCPY030)。
文摘Docker,as a mainstream container solution,adopts the Copy-on-Write(CoW)mechanism in its storage drivers.This mechanism satisfies the need of different containers to share the same image.However,when a single container performs operations such as modification of an image file,a duplicate is created in the upper readwrite layer,which contributes to the runtime overhead.When the accessed image file is fairly large,this additional overhead becomes non-negligible.Here we present the concept of Dynamic Prefetching Strategy Optimization(DPSO),which optimizes the Co W mechanism for a Docker container on the basis of the dynamic prefetching strategy.At the beginning of the container life cycle,DPSO pre-copies up the image files that are most likely to be copied up later to eliminate the overhead caused by performing this operation during application runtime.The experimental results show that DPSO has an average prefetch accuracy of greater than 78%in complex scenarios and could effectively eliminate the overhead caused by the CoW mechanism.
文摘针对大规模虚拟机环境下软件的按需部署,提出了一种基于预取的按需软件部署优化机制,能够降低用户端虚拟机的启动延迟以及为用户提供更好的虚拟机本地运行性能.基于用户使用软件的行为特点以及虚拟磁盘映像的细粒度分割,预取机制在后台对服务器端存储的虚拟磁盘映像进行预取,通过一种基于访问频率和优先级的预取目标识别算法AFPTR(access frequency and priority-based prefetch target recognition)和一种预取量动态调节机制,将预取集中在用户使用的少数小尺寸的虚拟磁盘映像上,并在预取过程中对预取量进行动态自适应地调节,以提高虚拟磁盘访问的本地命中率,进而提高用户端虚拟机的运行性能.基于QEMU虚拟机和Linux平台,实现了基于预取的按需软件部署原型系统.实验结果表明,预取机制能够有效地降低虚拟机的启动延迟,并能提高虚拟机的本地运行性能,支持虚拟机环境下按需、快速的软件部署.
