Hybrid mobility prediction of 802.11 infrastructure nodes by location tracking and data mining

Hdl Handle:
http://hdl.handle.net/10149/243785
Title:
Hybrid mobility prediction of 802.11 infrastructure nodes by location tracking and data mining
Authors:
Issac, B. (Biju); Hamid, K. (Khairuddin); Tan, C.E.
Affiliation:
University Malaysia Sarawak
Citation:
Issac, B., Hamid, K. & Tan, C.E. (2010) 'Hybrid mobility prediction of 802.11 infrastructure nodes by location tracking and data mining, Journal of Information Technology in Asia (JITA), 3(1), pp.9-24
Publisher:
Universiti Malaysia Sarawak
Journal:
Journal of IT in Asia
Issue Date:
2010
URI:
http://hdl.handle.net/10149/243785
Additional Links:
http://www.fcsit.unimas.my/jita/vol3/paper2.pdf
Abstract:
In an IEEE 802.11 Infrastructure network, as the mobile node is moving from one access point to another, the resource allocation and smooth hand off may be a problem. If some reliable prediction is done on mobile node’s next move, then resources can be allocated optimally as the mobile node moves around. This would increase the performance throughput of wireless network. We plan to investigate on a hybrid mobility prediction scheme that uses location tracking and data mining to predict the future path of the mobile node. We also propose a secure version of the same scheme. Through simulation and analysis, we present the prediction accuracy of our proposal.
Type:
Article
Language:
en
Keywords:
mobility prediction; mobility management; mobility patterns; location tracking; data mining
ISSN:
1823-5042
Citation Count:
No citation information available on Web of Science or Scopus

Full metadata record

DC FieldValue Language
dc.contributor.authorIssac, B. (Biju)en_GB
dc.contributor.authorHamid, K. (Khairuddin)-
dc.contributor.authorTan, C.E.-
dc.date.accessioned2012-09-13T10:09:55Z-
dc.date.available2012-09-13T10:09:55Z-
dc.date.issued2010-
dc.identifier.citationJournal of Information Technology in Asia; 3: 9-24en_GB
dc.identifier.issn1823-5042-
dc.identifier.urihttp://hdl.handle.net/10149/243785-
dc.description.abstractIn an IEEE 802.11 Infrastructure network, as the mobile node is moving from one access point to another, the resource allocation and smooth hand off may be a problem. If some reliable prediction is done on mobile node’s next move, then resources can be allocated optimally as the mobile node moves around. This would increase the performance throughput of wireless network. We plan to investigate on a hybrid mobility prediction scheme that uses location tracking and data mining to predict the future path of the mobile node. We also propose a secure version of the same scheme. Through simulation and analysis, we present the prediction accuracy of our proposal.en_GB
dc.language.isoenen
dc.publisherUniversiti Malaysia Sarawaken_GB
dc.relation.urlhttp://www.fcsit.unimas.my/jita/vol3/paper2.pdfen_GB
dc.subjectmobility predictionen_GB
dc.subjectmobility managementen_GB
dc.subjectmobility patternsen_GB
dc.subjectlocation trackingen_GB
dc.subjectdata miningen_GB
dc.titleHybrid mobility prediction of 802.11 infrastructure nodes by location tracking and data miningen
dc.typeArticleen
dc.contributor.departmentUniversity Malaysia Sarawaken_GB
dc.identifier.journalJournal of IT in Asiaen_GB
ref.citationcountNo citation information available on Web of Science or Scopusen_GB
or.citation.harvardIssac, B., Hamid, K. & Tan, C.E. (2010) 'Hybrid mobility prediction of 802.11 infrastructure nodes by location tracking and data mining, Journal of Information Technology in Asia (JITA), 3(1), pp.9-24en_GB
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