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Most Influential SIGCOMM 2017 Paper · 2026-03 edition

RotorNet: A Scalable, Low-complexity, Optical Datacenter Network

William M. Mellette, Rob McGuinness, Arjun Roy, Alex Forencich, George Papen, Alex C. Snoeren, George Porter

Venue
ACM SIGCOMM Conference (SIGCOMM) 2017
Recognition
Most Influential SIGCOMM 2017 Paper (Rank No. 10)
Edition
2026-03
Impact factor
5
Certificate ID
95b14cba8c18009b

Abstract

The ever-increasing bandwidth requirements of modern datacenters have led researchers to propose networks based upon optical circuit switches, but these proposals face significant deployment challenges. In particular, previous proposals dynamically configure circuit switches in response to changes in workload, requiring network-wide demand estimation, centralized circuit assignment, and tight time synchronization between various network elements--- resulting in a complex and unwieldy control plane. Moreover, limitations in the technologies underlying the individual circuit switches restrict both the rate at which they can be reconfigured and the scale of the network that can be constructed. We propose RotorNet, a circuit-based network design that addresses these two challenges. While RotorNet dynamically reconfigures its constituent circuit switches, it decouples switch configuration from traffic patterns, obviating the need for demand collection and admitting a fully decentralized control plane. At the physical layer, RotorNet relaxes the requirements on the underlying circuit switches---in particular by not requiring individual switches to implement a full crossbar---enabling them to scale to 1000s of ports. We show that RotorNet outperforms comparably priced Fat Tree topologies under a variety of workload conditions, including traces taken from two commercial datacenters. We also demonstrate a small-scale RotorNet operating in practice on an eight-node testbed.

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