Clustering mobile trajectories for resource allocation in mobile environments

buir.contributor.authorUlusoy, Özgür
dc.citation.epage329en_US
dc.citation.spage319en_US
dc.citation.volumeNumber2810en_US
dc.contributor.authorKatsaros, D.en_US
dc.contributor.authorNanopoulos, A.en_US
dc.contributor.authorKarakaya, M.en_US
dc.contributor.authorYavas, G.en_US
dc.contributor.authorUlusoy, Özgüren_US
dc.contributor.authorManolopoulos, Y.en_US
dc.date.accessioned2016-02-08T10:28:17Z
dc.date.available2016-02-08T10:28:17Zen_US
dc.date.issued2003en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractThe recent developments in computer and communication technologies gave rise to Personal Communication Systems. Due to the nature of the PCS, the bandwidth allocation problem arises, which is based on the notion of bandwidth-on-demand. We deal with the problem of how to predict the position of a mobile client. We propose a new algorithm, called DCP, to discover user mobility patterns from collections of recorded mobile trajectories and use them for the prediction of movements and dynamic allocation of resources. The performance of the proposed algorithm is examined against two baseline algorithms. The simulation results illustrate that the proposed algorithm achieves recall that is comparable to that of the baseline algorithms and substantial improvement in precision. This improvement guarantees very good predictions for resource allocation with the advantage of very low resource consumption. © Springer-Verlag Berlin Heidelberg 2003.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T10:28:17Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2003en_US
dc.identifier.doi10.1007/978-3-540-45231-7_30en_US
dc.identifier.issn0302-9743en_US
dc.identifier.issn1611-3349en_US
dc.identifier.urihttp://hdl.handle.net/11693/24366en_US
dc.language.isoEnglishen_US
dc.publisherSpringeren_US
dc.relation.isversionofhttps://doi.org/10.1007/978-3-540-45231-7_30en_US
dc.source.titleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_US
dc.subjectResource Allocationen_US
dc.subjectLocation Predictionen_US
dc.subjectMobile Clienten_US
dc.subjectBaseline Algorithmen_US
dc.subjectPaging Areaen_US
dc.titleClustering mobile trajectories for resource allocation in mobile environmentsen_US
dc.typeArticleen_US

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