基于sdn的云数据中心流量和虚拟机迁移优化吞吐量和能源

Wei-Chu Lin, Chien-Hui Liao, Kuan-Tsen Kuo, Charles H.-P. Wen
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引用次数: 18

摘要

最小化能源消耗和提高数据中心的性能对于云运营商节省成本至关重要,但传统上,这两个优化目标是分开处理的。因此,本文提出了一种结合流量迁移和虚拟机迁移两种策略的统一解决方案,以同时实现吞吐量最大化和能耗最小化。在软件定义网络(SDN)中,流量感知流迁移(Traffic-aware flow migration, FM)首先被纳入动态路由(DENDIST)中,并发展为DENDIST-FM,以提高吞吐量和避免拥塞。其次,在给定能量和拓扑信息的情况下,虚拟机迁移(ETA-VMM)可以在减少流量负载的同时节省能源。实验结果表明,与以往的工作相比,该方法平均提高了42.5%的吞吐量,而能耗仅为2.2%。因此,在基于sdn的云数据中心中,统一的流程和虚拟机迁移方案已被证明是有效的,可以优化吞吐量和能源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flow-and-VM Migration for Optimizing Throughput and Energy in SDN-Based Cloud Datacenter
Minimizing energy consumption and improving performance in data centers are critical to cost-saving for cloud operators, but traditionally, these two optimization objectives are treated separately. Therefore, this paper presents an unified solution combining two strategies, flow migration and VM migration, to maximize throughput and minimize energy, simultaneously. Traffic-aware flow migration (FM) is first incorporated in dynamic reroute (DENDIST), evolving into DENDIST-FM, in a software-defined network (SDN) for improving throughput and avoiding congestion. Second, given energy and topology information, VM migration (ETA-VMM) can help reduce traffic loads and meanwhile save energy. Our experimental result indicates that compared to previous works, the proposed method can improve throughput by 42.5% on average with only 2.2% energy overhead. Accordingly, the unified flow-and-VM migration solution has been proven effective for optimizing throughput and energy in SDN-based cloud data centers.
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