Efficient Data Center Flow Scheduling Without Starvation Using Expansion Ratio

Abstract

Existing data center transport protocols are usually based on the Processor Sharing (PS) policy and/or the Shortest Remaining Processing Time (SRPT) policy. PS divides link bandwidth equally between competing flows, thus it fails to achieve optimal average flow completion time (FCT). SRPT prioritizes flows that have the shortest remaining processing time and provides near-optimal average FCT, but it may cause long flows to suffer unfair delays, or even starve them. In fact, these two types of policies represent two directions in the design space: PS prefers fairness (in terms of starvation freedom) while SRPT favors efficiency (in terms of average FCT). In this paper, we propose a novel metric, expansion ratio, which enables us to strike a balance between SRPT and PS. We design MERP that achieves efficient flow scheduling without starvation. MERP takes care of both average and tail FCTs by minimizing the expansion ratio of competing flows in a lexicographically manner. MERP controls the sending rate of competing flows via synchronized virtual deadlines and routes flows in a downstream-aware manner that reacts quickly to link failures. We evaluate MERP using extensive NS2-based simulations. Results show that, under various traffic loads, MERP reduces the tail FCT significantly with a negligible increase of average FCT compared with pFabric, and MERP reduces the average FCT notably compared with ECMP and CONGA when link failures occur.