NDLI: Predictive distance-based mobility management for multidimensional PCS networks

Content Provider	ACM Digital Library
Author	Liang, Ben Haas, Zygmunt J.
Abstract	This paper presents a mobile tracking scheme that exploits the predictability of user mobility patterns in wireless PCS networks. In this scheme, a mobile's future location is predicted by the network, based on the information gathered from the mobile's recent report of location and velocity. When a call is made, the network pages the destination mobile around the predicted location. A mobile makes the same location prediction as the network does; it inspects its own location periodically and reports the new location when the distance between the predicted and the actual locations exceeds a threshold. To more realistically represent the various degrees of velocity correlation in time, a Gauss-Markov mobility model is used. For practical systems where the mobility pattern varies over time, we propose a dynamic Gauss-Markov parameter estimator that provides the mobility parameters to the prediction algorithm.Based on the Gauss-Markov model, we describe an analytical framework to evaluate the cost of mobility management for the proposed scheme. We also present an approximation method that reduces the computational complexity of the cost evaluation for multidimensional systems. We then compare the cost of predictive mobility management against that of the regular, nonpredictive distance-based scheme, for both the case with ideal Gauss-Markov mobility pattern and the case with time-varying mobility pattern.The performance advantage of the proposed scheme is demonstrated under various mobility patterns, call patterns, location inspection cost, location updating cost, mobile paging cost, and frequencies of mobile location inspections. As a point of reference, prediction can reduce the mobility management cost by more than 50% for all systems, where a the mobile users have moderate mean velocity and where performing a single location update is as least as expensive as paging a mobile in one cell.
Starting Page	718
Ending Page	732
Page Count	15
File Format	PDF
ISSN	10636692
DOI	10.1109/TNET.2003.815301
Volume Number	11
Issue Number	5
Journal	IEEE/ACM Transactions on Networking (TON)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2003-10-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Gauss-Markov model Distance-based location management Dynamic parameter estimation Fluid flow Mobility pattern Predictive mobility management Random walk Wireless networking
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Networks and Communications Software Computer Science Applications

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