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Methodologies for generating HTTP streaming video workloads to evaluate web server performance

Published: 04 June 2012 Publication History

Abstract

Recent increases in live and on-demand video streaming have dramatically changed the Internet landscape. In North America, Netflix alone accounts for 28% of all and 33% of peak downstream Internet traffic on fixed access links, with further rapid growth expected [26]. This increase in streaming traffic coincides with the steady adoption of HTTP for use in video streaming. Many streaming video providers, such as Apple, Adobe, Akamai, Netflix and Microsoft, now use HTTP to stream content [5]. Therefore, it is critical that we understand the impact of this emerging workload on web servers. Unlike other web content, a recent study [13] of streaming video shows that even small infrequent latency spikes, manifested as buffering related pauses, can result in shorter viewing times especially during live broadcasts. Unfortunately, no appropriate benchmarks exist to evaluate web servers under HTTP video streaming workloads.
In this paper, we devise tools and methodologies for generating workloads and benchmarks for video streaming systems. We describe the difficulties encountered in trying to utilize existing workload characterization studies, motivate the need for workloads, and create example benchmarks. We use these benchmarks to examine the performance of three existing web servers (Apache, nginx, and userver). We find that simple modifications to userver provide promising and significant benefits on some representative streaming workloads. While these results warrant additional investigation, they demonstrate the need for and value of HTTP video streaming benchmarks in web server development.

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  • (2020)A scalable load generation framework for evaluation of video streaming workflows in the cloudProceedings of the 11th ACM Multimedia Systems Conference10.1145/3339825.3394930(255-260)Online publication date: 27-May-2020
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cover image ACM Other conferences
SYSTOR '12: Proceedings of the 5th Annual International Systems and Storage Conference
June 2012
183 pages
ISBN:9781450314480
DOI:10.1145/2367589
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • The Technion - Israel Institute of Techn.: The Technion - Israel Institute of Technology

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New York, NY, United States

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Published: 04 June 2012

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Overall Acceptance Rate 108 of 323 submissions, 33%

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  • (2023)TADRP: Toward Thermal-Aware Data Replica Placement in Data-Intensive Data CentersIEEE Transactions on Network and Service Management10.1109/TNSM.2023.326386420:4(4397-4415)Online publication date: Dec-2023
  • (2022)A Thermal-Aware Data Replica Placement Strategy for Data-Intensive Data CentersProceedings of the International Conference on Parallel Architectures and Compilation Techniques10.1145/3559009.3569679(540-541)Online publication date: 8-Oct-2022
  • (2020)A scalable load generation framework for evaluation of video streaming workflows in the cloudProceedings of the 11th ACM Multimedia Systems Conference10.1145/3339825.3394930(255-260)Online publication date: 27-May-2020
  • (2020)PRIMA: Subscriber-Driven Interference Mitigation for Cloud ServicesIEEE Transactions on Network and Service Management10.1109/TNSM.2019.296161317:2(958-971)Online publication date: Jun-2020
  • (2020)A Survey on Adaptive 360° Video Streaming: Solutions, Challenges and OpportunitiesIEEE Communications Surveys & Tutorials10.1109/COMST.2020.300699922:4(2801-2838)Online publication date: Dec-2021
  • (2019)Caching Salon: From Classical to Learning-Based Approaches2019 IEEE International Conference on Service-Oriented System Engineering (SOSE)10.1109/SOSE.2019.00046(269-2695)Online publication date: Apr-2019
  • (2019)Building Autonomic Elements from Video-Streaming ServersJournal of Network and Systems Management10.1007/s10922-019-09503-1Online publication date: 16-Jul-2019
  • (2018)Disk Prefetching Mechanisms for Increasing HTTP Streaming Video Server ThroughputACM Transactions on Modeling and Performance Evaluation of Computing Systems10.1145/31645363:2(1-30)Online publication date: 22-Mar-2018
  • (2018)Subscriber-Driven Cloud Interference Mitigation for Network Services2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)10.1109/IWQoS.2018.8624154(1-6)Online publication date: Jun-2018
  • (2018)Workload Generators for Web-Based Systems: Characteristics, Current Status, and ChallengesIEEE Communications Surveys & Tutorials10.1109/COMST.2018.279864120:2(1526-1546)Online publication date: Oct-2019
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