Fast Link Failure Detection in Datacenter

• Main Authors: Wun-Sin Wu, 吳文心
• Other Authors: Guey-Yun Chang
• Format: Others
• Language: en_US
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/69299401639114331025

碩士 === 國立中央大學 === 資訊工程學系 === 105 === Load balancing is an important technique to cope with dynamic and unpredictable traffic demands in data center networks. In general, load balancing schemes aim to split traffics evenly among multiple paths. However, most existing approaches either suffers from packet reordering (which may confuse TCP congestion control) or fail to quick response (i.e., coarse slicing granularity). Recently, FLARE introduced a burst (called flowlet) based traffic splitting, which attains responsiveness without causing packet reordering. However, the very high bandwidth of internal datacenter flows suggests that the gaps needed for flowlets may be rare. Besides, in Flare, splitting granularity increases (i.e., coarse granularity) when flow size increases. In this paper, we propose an artificial flowlet-based load balancing algorithm which can maintain fine-granularity (even in large flows) and can also avoid packet reordering. Our scheme has at least 20% improvement in flow completion time under the same incidence of packet reordering.