Article in Proceedings INPROC-2006-46

BibliographyBürklen, Susanne; Marrón, Pedro José; Rothermel, Kurt; Pfahl, Timo: Hoarding Location-Based Data Using Clustering.
In: Proceedings of the 4-th ACM International Workshop on Mobility Management and Wireless Access Protocols (MobiWAC 2006); Torremolinos, Spain, Oct. 2, 2006.
University of Stuttgart : Collaborative Research Center SFB 627 (Nexus: World Models for Mobile Context-Based Systems).
pp. 1-1, english.
Sheridan Printing, October 2, 2006.
Article in Proceedings (Conference Paper).
CR-SchemaH.3 (Information Storage and Retrieval)
Abstract

The proliferation of mobile devices and the fact that high-bandwidth and continuous connectivity is not available everywhere, has led to the creation of hoarding algorithms that attempt to mitigate the problems related with disconnected operation and with the operation in areas where bandwidth is either scarce or expensive. In this paper, we present a hoarding scheme for location-based data in semi-structured information spaces, such as the World Wide Web, which relies on clustering of semantically related data items. We show by means of experimental evaluation that our clustering-based approach outperforms existing hoarding techniques that do not make use of clustering by a factor of more than 2 in terms of hoard cache hit ratio.

Department(s)University of Stuttgart, Institute of Parallel and Distributed Systems, Distributed Systems
Project(s)SFB-627, A2 (University of Stuttgart, Institute of Parallel and Distributed Systems, Distributed Systems)
Entry dateAugust 1, 2006
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