Hardware-Software Co-Design for Network Performance Measurement
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Hardware-software.pdf
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274.57 KB
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Author(s)
Walker, David
Rexford, Jennifer
Jeyakumar, Vimalkumar
Kim, Changhoon
Narayana Ganapathy, Srinivas
Sivaraman Kaushalram, Anirudh
Nathan, Vikram
Alizadeh Attar, Mohammadreza
Date Issued
November 2016
Journal
Proceedings of the 15th ACM Workshop on Hot Topics in Networks - HotNets '16
Publisher
Association for Computing Machinery (ACM)
Citation
Narayana, Srinivas et al. “Hardware-Software Co-Design for Network Performance Measurement.” Proceedings of the 15th ACM Workshop on Hot Topics in Networks, Atlanta, GA, USA, 9-10 November, 2016. ACM Press, 2016. pp.190–196.
Version
Author's final manuscript
Abstract
Diagnosing performance problems in networks is important, for example to determine where packets experience high latency or loss. However, existing performance diagnoses are constrained by limited switch mechanisms for measurement. Alternatively, operators use endpoint information indirectly to infer root causes for problematic latency or drops.
Instead of designing piecemeal solutions to work around such switch restrictions, we believe that the right approach is to co-design language abstractions and switch hardware primitives for network performance measurement. This approach provides confidence that the switch primitives are sufficiently general, i.e., they can support a variety of existing and unanticipated use cases.
We present a declarative query language that allows operators to ask a diverse set of network performance questions. We show that these queries can be implemented efficiently in switch hardware using a novel programmable key-value store primitive. Our preliminary evaluations show that our hardware design is feasible at modest chip area overhead relative to existing switching chips.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1145/3005745.3005775
