一种感知多资源共享的虚拟机最大化逼近算法

Safraz Rampersaud, Daniel Grosu
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引用次数: 8

摘要

云提供商面临的挑战是,如何在分配请求的同时最小化资源消耗,从而实现利润最大化,从而有效地管理其基础设施。我们通过设计一个贪心逼近算法来解决多资源共享感知虚拟机最大化(MSAVMM)问题来解决这一挑战。MSAVMM问题需要确定可以在给定服务器上实例化的虚拟机集,以便从托管虚拟机中获得的利润最大化。此问题的解决方案必须考虑虚拟机之间的内存页面共享以及虚拟机请求的每种资源的有限容量。我们通过确定其近似比率并通过对其他共享感知VM分配算法进行广泛的实验来分析所提出算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Multi-resource Sharing-Aware Approximation Algorithm for Virtual Machine Maximization
Cloud providers face the challenge of efficiently managing their infrastructure through minimizing resource consumption while allocating requests such that their profit is maximized. We address this challenge by designing a greedy approximation algorithm for solving the multi-resource sharing-aware virtual machine maximization (MSAVMM) problem. The MSAVMM problem requires determining the set of VMs that can be instantiated on a given server such that the profit derived from hosting the VMs is maximized. The solution to this problem has to consider the sharing of memory pages among VMs and the restricted capacities of each type of resource requested by the VMs. We analyze the performance of the proposed algorithm by determining its approximation ratio and by performing extensive experiments against other sharing-aware VM allocation algorithms.
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