Tailor: Trimming Coflow Completion Times in Datacenter Networks
Jingjie Jiang, Shiyao Ma, Bo Li, Baochun Li · 2016
Tasks in a data-parallel job communicate with each other through a number of concurrent flows, which is described as a coflow. These flows are correlated in the sense that the performance of a coflow is dictated by the flow that takes the longest time to complete. Minimizing coflow completion times, however, turns out to be a challenge, given the correlation across flows and how they are routed collectively through a datacenter network. In this paper, we propose Tailor, a simple yet effective mechanism with the objective of trimming the coflow completion times in a datacenter network. To achieve our objective, Tailor takes advantage of OpenFlow in a software-defined datacenter network. By monitoring and rerouting live flows to links with lighter loads, Tailor guarantees that the coflow completion time is minimized dynamically and converges to its lower bound. Our experimental results in both Mininet and large-scale simulations have shown that Tailor is much more effective than flow-level schemes when it comes to reducing coflow completion times. It also outperforms existing scheduling-only coflow mechanisms and achieves similar performance with the state-of-the-art hybrid mechanism, yet with much lower complexity.