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FlowBender: Flow-level Adaptive Routing for Improved Latency and Throughput in Datacenter Networks

Published:02 December 2014Publication History

ABSTRACT

Datacenter networks provide high path diversity for traffic between machines. Load balancing traffic across these paths is important for both, latency- and throughput-sensitive applications. The standard load balancing techniques used today obliviously hash a flow to a random path. When long flows collide on the same path, this might lead to long lasting congestion while other paths could be underutilized, degrading performance of other flows as well. Recent proposals to address this shortcoming incur significant implementation complexity at the host that would actually slow down short flows (MPTCP), depend on relatively slow centralized controllers for rerouting large congesting flows (Hedera), or require custom switch hardware, hindering near-term deployment (DeTail).

We propose FlowBender, a novel technique that: (1) Load balances distributively at the granularity of flows instead of packets, avoiding excessive packet reordering. (2) Uses end-host-driven rehashing to trigger dynamic flow-to-path assignment. (3) Recovers from link failures within a Retransmit Timeout (RTO). (4) Amounts to less than 50 lines of critical kernel code and is readily deployable in commodity data centers today. (5) Is very robust and simple to tune. We evaluate FlowBender using both simulations and a real testbed implementation, and show that it improves average and tail latencies significantly compared to state of the art techniques without incurring the significant overhead and complexity of other load balancing schemes.

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    • Published in

      cover image ACM Conferences
      CoNEXT '14: Proceedings of the 10th ACM International on Conference on emerging Networking Experiments and Technologies
      December 2014
      438 pages
      ISBN:9781450332798
      DOI:10.1145/2674005

      Copyright © 2014 Owner/Author

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      Publication History

      • Published: 2 December 2014

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      CoNEXT '14 Paper Acceptance Rate27of133submissions,20%Overall Acceptance Rate198of789submissions,25%

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