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Bandwidth allocation for communicating virtual machines in cloud data centers

机译:用于云数据中心中的虚拟机传播虚拟机的带宽分配

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High-performance computing in a cloud environment may require massive data transfer among some of the virtual machines (VMs). These VMs are deployed in physical machines (hosts) of a data center. The data transfer among the communicating VMs may use the same shared communication links of the data center. Hence, it is important to have efficient bandwidth allocation policies for different data transfer requests (DTRs) which result in better utilization of bandwidth and fair allocation among the DTRs. In this paper, a few bandwidth allocation policies are proposed and their performances are analyzed. While designing these policies, the objective is the maximization of throughput and bandwidth utilization while minimizing the service time and turnaround time. Some of the policies are based on integer linear programming (ILP) which runs in exponential time while others are based on polynomial-time heuristics. Experimental results show that the performances of heuristic-based policies are comparable to those given by ILP-based exponential time policies.
机译:在云环境中的高性能计算可能需要在某些虚拟机(VM)中的大量数据传输。这些VM部署在数据中心的物理机(主机)中。通信VM之间的数据传输可以使用数据中心的相同共享通信链路。因此,重要的是具有用于不同数据传输请求(DTR)的有效带宽分配策略,这导致DTR之间的带宽和公平分配更好地利用带宽和公平分配。在本文中,提出了一些带宽分配策略,分析了它们的性能。在设计这些政策时,目标是吞吐量和带宽利用率的最大化,同时最小化服务时间和周转时间。一些策略基于整数线性编程(ILP),其在指数时间内运行,而其他政策则基于多项式时间启发式。实验结果表明,由基于ILP的指数时间策略给出的基于启发式的政策的性能。

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