Scheduling Mix-flows in Commodity Datacenters with Karuna
Name
Scheduling mix-flows.pdf
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650.76 KB
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Author(s)
Chen, Li
Chen, Kai
Bai, Wei
Alizadeh Attar, Mohammadreza
Date Issued
August 2016
Journal
Proceedings of the 2016 conference on ACM SIGCOMM 2016 Conference - SIGCOMM '16
Publisher
Association for Computing Machinery (ACM)
Citation
Chen, Li et al. “Scheduling Mix-Flows in Commodity Datacenters with Karuna.” Proceedings of the 2016 ACM SIGCOMM Conference, Florianopolis, Brazil, 22-26 August, 2016. ACM Press, 2016, pp. 174–187.
Version
Author's final manuscript
Abstract
Cloud applications generate a mix of flows with and without deadlines. Scheduling such mix-flows is a key challenge; our experiments show that trivially combining existing schemes for deadline/non-deadline flows is problematic. For example, prioritizing deadline flows hurts flow completion time (FCT) for non-deadline flows, with minor improvement for
deadline miss rate. We present Karuna, a first systematic solution for scheduling mix-flows. Our key insight is that deadline flows should
meet their deadlines while minimally impacting the FCT of non-deadline flows. To achieve this goal, we design a novel Minimal-impact Congestion control Protocol (MCP) that handles
deadline flows with as little bandwidth as possible. For
non-deadline flows, we extend an existing FCT minimization scheme to schedule flows with known and unknown sizes. Karuna requires no switch modifications and is backward compatible with legacy TCP/IP stacks. Our testbed experiments and simulations show that Karuna effectively schedules mix-flows, for example, reducing the 95th percentile FCT of non-deadline flows by up to 47.78% at high load compared to pFabric, while maintaining low (<5.8%) deadline miss rate.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/2934872.2934888
