Mahimahi: Accurate record-and-replay for http

Ravi Netravali, Anirudh Sivaraman, Somak Das, Ameesh Goyal, Keith Winstein, James Mickens, Hari Balakrishnan

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

279 Scopus citations

Abstract

This paper presents Mahimahi, a framework to record traffic from HTTP-based applications, and later replay it under emulated network conditions. Mahimahi improves upon prior record-and-replay frameworks in three ways. First, it is more accurate because it carefully emulates the multi-server nature of Web applications, present in 98% of the Alexa US Top 500 Web pages. Second, it isolates its own network traffic, allowing multiple Mahimahi instances emulating different networks to run concurrently without mutual interference. And third, it is designed as a set of composable shells, providing ease-of-use and extensibility. We evaluate Mahimahi by: (1) analyzing the performance of HTTP/1.1, SPDY, and QUIC on a corpus of 500 sites, (2) using Mahimahi to understand the reasons why these protocols are suboptimal, (3) developing Cumulus, a cloud-based browser designed to overcome these problems, using Mahimahi both to implement Cumulus by extending one of its shells, and to evaluate it, (4) using Mahimahi to evaluate HTTP multiplexing protocols on multiple performance metrics (page load time and speed index), and (5) describing how others have used Mahimahi.

Original languageEnglish (US)
Title of host publicationProceedings of the 2015 USENIX Annual Technical Conference, USENIX ATC 2015
PublisherUSENIX Association
Pages417-429
Number of pages13
ISBN (Electronic)9781931971225
StatePublished - 2015
Externally publishedYes
Event2015 USENIX Annual Technical Conference, USENIX ATC 2015 - Santa Clara, United States
Duration: Jul 8 2015Jul 10 2015

Publication series

NameProceedings of the 2015 USENIX Annual Technical Conference, USENIX ATC 2015

Conference

Conference2015 USENIX Annual Technical Conference, USENIX ATC 2015
Country/TerritoryUnited States
CitySanta Clara
Period7/8/157/10/15

All Science Journal Classification (ASJC) codes

  • General Computer Science

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