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Minimizing Latency in Fetching Virtual Machine Images Based on Multi-point Collaborative Approach

机译:基于多点协作方法的虚拟机映像获取中的延迟最小化

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摘要

Cloud computing centers enable to provision diverse virtual machine (VM) in an elastic and scalable manner. VMs are created by instantiating VM images that encapsulate the required applications or services with their support environment. The multi-gigabyte VM images are hosted in the central image repository, while hosting centers are geographically dispersed. Thus, to fetch a GigaByte sized VM image from a repository over the Internet is time consuming. To address this problem, we first take advantage of high degree of commonality of VM images, and divide the VM images into fine-grain chunks by designing a mixed chunk scheme. And then, based on chunk-level sharing among different images, we propose a novel VM images acquisition scheme based on multi-point collaboration (MPCA), which minimizes latency in fetching VM images. Our experiments show that our proposed scheme can largely reduce request service time. Moreover, it can efficiently decentralize network traffic load, reduce the contention result from additional traffic introduced in the network, especially when traffic load is heavy.
机译:云计算中心能够以弹性和可扩展的方式配置各种虚拟机(VM)。通过实例化包含所需应用程序或服务及其支持环境的VM映像来创建VM。数千兆字节的VM映像托管在中央映像存储库中,而托管中心则在地理位置上分散。因此,要通过Internet从存储库中提取千兆字节大小的VM映像非常耗时。为了解决这个问题,我们首先利用VM映像的高度通用性,并通过设计混合块方案将VM映像划分为细粒度的块。然后,基于不同图像之间的块级共享,我们提出了一种基于多点协作(MPCA)的新颖的VM图像采集方案,该方案可最大程度地减少获取VM图像的延迟。我们的实验表明,我们提出的方案可以大大减少请求服务时间。而且,它可以有效地分散网络流量负载,减少由网络中引入的额外流量引起的竞争结果,尤其是在流量负载很重的情况下。

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