Micro load balancing in data centers with DRILL

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Abstract

The trend towards simple data center network fabric strips most network functionality, including load balancing capabilities, out of the network core and pushes them to the edge. We investigate a different direction of incorporating minimal load balancing intelligence into the network fabric and show that this slightly smarter fabric significantly enhances performance. We provide a very simple in-network load balancing scheduling algorithm called DRILL which is purely local to each switch. DRILL leverages local load sensing and randomization concepts to distribute load among multiple paths. Through simulation, we show that this simple approach outperforms CONGA, a recent global edge-based load balancing scheme for data centers. We also formally prove the switch-level stability and throughput-efficiency of DRILL's scheduling algorithm.

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Ghorbani, S., Godfrey, B., Ganjali, Y., & Firoozshahian, A. (2015). Micro load balancing in data centers with DRILL. In Proceedings of the 14th ACM Workshop on Hot Topics in Networks, HotNets-XIV 2015. Association for Computing Machinery. https://doi.org/10.1145/2834050.2834107

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