Scheduling mix-flows in commodity datacenters with Karuna

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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.

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APA

Chen, L., Chen, K., Bai, W., & Alizadeh, M. (2016). Scheduling mix-flows in commodity datacenters with Karuna. In SIGCOMM 2016 - Proceedings of the 2016 ACM Conference on Special Interest Group on Data Communication (pp. 174–187). Association for Computing Machinery, Inc. https://doi.org/10.1145/2934872.2934888

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