TY - GEN
T1 - Reco
T2 - 39th IEEE International Conference on Distributed Computing Systems, ICDCS 2019
AU - Zhang, Chi
AU - Tan, Haisheng
AU - Xu, Chao
AU - Li, Xiang Yang
AU - Tang, Shaojie
AU - Li, Yupeng
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - To improve the application-level data efficiency, the scheduling of coflows, defined as a collection of parallel flows sharing the same objective, is prevailing in recent data centers. Meanwhile, optical circuit switches (OCS) are gradually applied to provide high data rate with low power consumption. However, so far few research outputs have covered the flow scheduling in the context of OCS, let alone the coflow scheduling problems. In this paper, we investigate coflow scheduling in the OCS-based data centers. We first derive a novel operation called regularization processed respectively on the flow traffic demands and the flow start times. Regularization can be efficiently implemented and reduce the circuit reconfiguration frequency dramatically. We then propose a 2-approximation algorithm, called Reco-Sin, for single coflow scheduling to minimize the coflow completion time (CCT). For multiple coflows, we derive another approximation algorithm, called Reco-Mul, to minimize the total weighted CCT, which can transform any non-preemptive multi-coflow scheduling in packet switches to that in OCS. Extensive simulations based on Facebook data traces show that Reco-Sin and Reco-Mul outperform state-of-the-art schemes significantly, i.e., one single coflow can be finished up to 2.72× faster with Reco-Sin, and multiple coflows can be completed up to 3.44× faster with Reco-Mul.
AB - To improve the application-level data efficiency, the scheduling of coflows, defined as a collection of parallel flows sharing the same objective, is prevailing in recent data centers. Meanwhile, optical circuit switches (OCS) are gradually applied to provide high data rate with low power consumption. However, so far few research outputs have covered the flow scheduling in the context of OCS, let alone the coflow scheduling problems. In this paper, we investigate coflow scheduling in the OCS-based data centers. We first derive a novel operation called regularization processed respectively on the flow traffic demands and the flow start times. Regularization can be efficiently implemented and reduce the circuit reconfiguration frequency dramatically. We then propose a 2-approximation algorithm, called Reco-Sin, for single coflow scheduling to minimize the coflow completion time (CCT). For multiple coflows, we derive another approximation algorithm, called Reco-Mul, to minimize the total weighted CCT, which can transform any non-preemptive multi-coflow scheduling in packet switches to that in OCS. Extensive simulations based on Facebook data traces show that Reco-Sin and Reco-Mul outperform state-of-the-art schemes significantly, i.e., one single coflow can be finished up to 2.72× faster with Reco-Sin, and multiple coflows can be completed up to 3.44× faster with Reco-Mul.
KW - Coflow Scheduling
KW - Data Center Networks
KW - Optical Circuit Switches
UR - https://www.scopus.com/pages/publications/85074853482
U2 - 10.1109/ICDCS.2019.00020
DO - 10.1109/ICDCS.2019.00020
M3 - Conference contribution
AN - SCOPUS:85074853482
T3 - Proceedings - International Conference on Distributed Computing Systems
SP - 111
EP - 121
BT - Proceedings - 2019 39th IEEE International Conference on Distributed Computing Systems, ICDCS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 7 July 2019 through 9 July 2019
ER -