Computer Science

Generalized sketch families for network traffic measurement

Document Type

Conference Paper

Abstract

Traffic measurement provides critical information for network management, resource allocation, traffic engineering, and attack detection. Most prior art has been geared towards specific application needs with specific performance objectives. To support diverse requirements with efficient and future-proof implementation, this paper takes a new approach to establish common frameworks, each for a family of traffic measurement solutions that share the same implementation structure, providing a high level of generality, for both size and spread measurements and for all flows. The designs support many options of performance-overhead tradeoff with as few as one memory update per packet and as little space as several bits per flow on average. Such a family-based approach will unify implementation by removing redundancy from different measurement tasks and support reconfigurability in a plug-n-play manner. We demonstrate the connection and difference in the design of these traffic measurement families and perform experimental comparisons on hardware/software platforms to find their tradeoff, which provide practical guidance for which solutions to use under given performance goals.

Publication Title

SIGMETRICS Performance 2020 - Abstracts of the 2020 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems

Publication Date

2020

First Page

63

Last Page

64

ISBN

9781450379854

DOI

10.1145/3393691.3394191

Keywords

big network data, generalized sketch families, network traffic measurement

APA Citation

Zhou, Y., Zhang, Y., Ma, C., Chen, S., & Odegbile, O. O. (2019). Generalized sketch families for network traffic measurement. Proceedings of the ACM on Measurement and Analysis of Computing Systems, 3(3), 1-34.

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