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Caching for IPTV distribution with time-shift
Swedish Institute of Computer Science, Kista, Sweden. (IS)
Mälardalen University, School of Innovation, Design and Engineering. (IS)ORCID iD: 0000-0002-2419-2735
2013 (English)In: 2013 International Conference on Computing, Networking and Communications, ICNC 2013, IEEE , 2013, 916-921 p.Conference paper, Published paper (Refereed)
Abstract [en]

Today video and TV distribution dominate Internet traffic and the increasing demand for high-bandwidth multimedia services puts pressure on Internet service providers. In this paper we simulate TV distribution with time-shift and investigate the effect of introducing a local cache close to the viewers. We study what impact TV program popularity, program set size, cache replacement policy and other factors have on the caching efficiency. The simulation results show that introducing a local cache close to the viewers significantly reduces the network load from TV-on-Demand services. By caching 4% of the program volume we can decrease the peak load during prime time by almost 50%. We also show that the TV program type and how program popularity changes over time can have a big influence on cache hit ratios and the resulting link loads

Place, publisher, year, edition, pages
IEEE , 2013. 916-921 p.
National Category
Computer Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-16105DOI: 10.1109/ICCNC.2013.6504212Scopus ID: 2-s2.0-84877597829ISBN: 978-146735288-8 (print)OAI: oai:DiVA.org:mdh-16105DiVA: diva2:565255
Conference
2013 International Conference on Computing, Networking and Communications, ICNC 2013; San Diego, CA; United States; 28 January 2013 through 31 January 2013
Available from: 2012-11-06 Created: 2012-11-06 Last updated: 2016-03-10Bibliographically approved
In thesis
1. Network overload avoidance by traffic engineering and content caching
Open this publication in new window or tab >>Network overload avoidance by traffic engineering and content caching
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The Internet traffic volume continues to grow at a great rate, now driven by video and TV distribution. For network operators it is important to avoid congestion in the network, and to meet service level agreements with their customers.  This thesis presents work on two methods operators can use to reduce links loads in their networks: traffic engineering and content caching.

This thesis studies access patterns for TV and video and the potential for caching.  The investigation is done both using simulation and by analysis of logs from a large TV-on-Demand system over four months.

The results show that there is a small set of programs that account for a large fraction of the requests and that a comparatively small local cache can be used to significantly reduce the peak link loads during prime time. The investigation also demonstrates how the popularity of programs changes over time and shows that the access pattern in a TV-on-Demand system very much depends on the content type.

For traffic engineering the objective is to avoid congestion in the network and to make better use of available resources by adapting the routing to the current traffic situation. The main challenge for traffic engineering in IP networks is to cope with the dynamics of Internet traffic demands.

This thesis proposes L-balanced routings that route the traffic on the shortest paths possible but make sure that no link is utilised to more than a given level L. L-balanced routing gives efficient routing of traffic and controlled spare capacity to handle unpredictable changes in traffic.  We present an L-balanced routing algorithm and a heuristic search method for finding L-balanced weight settings for the legacy routing protocols OSPF and IS-IS. We show that the search and the resulting weight settings work well in real network scenarios.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2012
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 133
National Category
Computer Engineering
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-16107 (URN)978-91-7585-087-1 (ISBN)
Public defence
2012-12-19, Kappa, Mälardalens högskola, Västerås, 13:15 (English)
Opponent
Supervisors
Available from: 2012-11-07 Created: 2012-11-06 Last updated: 2012-11-19Bibliographically approved

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CiteExportLink to record
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Citation style
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