Achieving High Utilization for Approximate Fair Queueing in Data Center

Modern data centers often host multiple applications with diverse network demands. To provide fair bandwidth allocation to several thousand traversing flows, Approximate Fair Queueing (AFQ) utilizes multiple priority queues in switch to approximate ideal fair queueing. However, due to limited number...

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Bibliographic Details
Published in2020 IEEE 40th International Conference on Distributed Computing Systems (ICDCS) pp. 932 - 942
Main Authors Liu, Jingling, Huang, Jiawei, Jiang, Ning, Li, Weihe, Wang, Jianxin
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2020
Subjects
Channel allocation
Computational modeling
Conferences
data center
Data centers
Distributed databases
fair queueing
link utilization
Packet loss
Switches
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Summary:Modern data centers often host multiple applications with diverse network demands. To provide fair bandwidth allocation to several thousand traversing flows, Approximate Fair Queueing (AFQ) utilizes multiple priority queues in switch to approximate ideal fair queueing. However, due to limited number of queues in commodity switches, AFQ easily experiences high packet loss and low link utilization. In this paper, we propose Elastic Fair Queueing (EFQ), which leverages limited priority queues to flexibly achieve both high network utilization and fair bandwidth allocation. EFQ dynamically assigns the free buffer space in priority queues for each packet to obtain high utilization without sacrificing flow-level fairness. The results of simulation experiments and real implementations show that EFQ reduces the average flow completion time by up to 82% over the state-of-the-art fair bandwidth allocation mechanisms.
ISSN:2575-8411
DOI:10.1109/ICDCS47774.2020.00099