Flow-and-VM migration for optimizing throughput and energy in SDN-based cloud datacenter

Wei Chu Lin, Chien Hui Liao, Kuan Tsen Kuo, Charles H.P. Wen

Research output: Contribution to journalConference article

11 Scopus citations

Abstract

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.

Original languageEnglish
Article number6753799
Pages (from-to)206-211
Number of pages6
JournalProceedings of the International Conference on Cloud Computing Technology and Science, CloudCom
Volume1
DOIs
StatePublished - 1 Jan 2013
Event5th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2013 - Bristol, United Kingdom
Duration: 2 Dec 20135 Dec 2013

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