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

Issac, Biju, Hamid, Khairuddin and Tan, C. E. (2010) Hybrid mobility prediction of 802.11 infrastructure nodes by location tracking and data mining. Journal of Information Technology in Asia, 3 (1). ISSN 1623-5042

[img]
Preview
Text
31-Article Text-89-1-10-20160420.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial 4.0.

Download (634kB) | Preview
Official URL: http://publisher.unimas.my/ojs/index.php/JITA/arti...

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.

Item Type: Article
Uncontrolled Keywords: Mobility prediction, mobility management, mobility patterns, location tracking, data mining
Subjects: G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 07 Jan 2019 10:11
Last Modified: 07 Jan 2019 10:15
URI: http://nrl.northumbria.ac.uk/id/eprint/37475

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics


Policies: NRL Policies | NRL University Deposit Policy | NRL Deposit Licence