A scalable architecture for maintaining packet latency measurements

Myungjin Lee, Nick Duffield, Ramana Rao Kompella

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Latency has become an important metric for network monitoring since the emergence of new latency-sensitive applications (e.g., algorithmic trading and high-performance computing). In this paper, to provide latency measurements at both finer (e.g., packet) as well as flexible (e.g., flow subsets) levels of granularity, we propose an architecture called MAPLE that essentially stores packet-level latencies in routers and allows network operators to query the latency of arbitrary traffic sub-populations. MAPLE is built using a scalable data structure called SVBF with small storage needs.
Original languageEnglish
Title of host publicationProceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems
Place of PublicationNew York, NY, USA
PublisherACM
Pages391-392
Number of pages2
ISBN (Print)978-1-4503-1097-0
DOIs
Publication statusPublished - 2012

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