Reputation-based content dissemination for user generated wireless podcasting

Liang Hu, Lars Dittmann, J.-Y. Le Boudec

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearch

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Abstract

User-generated podcasting service over human-centric opportunistic network can facilitate user-generated content sharing while humans are on the move beyond the coverage of infrastructure networks. We focus on the aspects of designing efficient forwarding and cache replacement schemes of such service under the constraints of limited capability of handheld device and limited network capacity. In particular, the design of those schemes is challenged by the lack of podcast channel popularity information at each node which is crucial for forwarding and caching decisions. We design a distributed reputation system based on modified Bayesian framework that enable each node estimates the channel popularity in a efficient way. It estimates channel popularity by not only first hand observations but also second hand observations from other nodes. Our simulation result shows reputation system can always well estimate most popular, intermediate and low popular channels, compare to history-based rank scheme which can only well estimate a few most popular channels. Reputation system significantly outperforms history-based rank when the public cache size is small or "a" parameter of Zipf-like distribution is small.
Original languageEnglish
Title of host publicationProceedings, WCNC
PublisherIEEE
Publication date2009
Pages1-6
ISBN (Print)978-1-4244-2947-9
DOIs
Publication statusPublished - 2009
EventIEEE Wireless Communications and Networking Conference 2009 - Budapest, Hungary
Duration: 5 Apr 20098 Apr 2009
http://wcnc2009.ieee-wcnc.org/

Conference

ConferenceIEEE Wireless Communications and Networking Conference 2009
Country/TerritoryHungary
CityBudapest
Period05/04/200908/04/2009
Internet address

Bibliographical note

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