|Title:||Flow-and-VM Migration for Optmizing Throughput and Energy in SDN-based Cloud Datacenter|
Wen, Charles H-P.
Undergraduate Honors Program of Electrical Engineering and Computer Science
|Abstract:||Minimizing energy consumption and improving performance in datacenters 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 datacenters.|
|Journal:||2013 IEEE FIFTH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING TECHNOLOGY AND SCIENCE (CLOUDCOM), VOL 1|
|Appears in Collections:||Conferences Paper|