Cart (Loading....) | Create Account
Close category search window

On location tracking and load balancing in cellular mobile environment-a probabilistic approach

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
2 Author(s)
Mitra, S. ; Dept. of Comput. Sc.& Tech., Bengal Eng. Sci. Univ. ; DasBit, S.

The present work addresses probabilistic solution of two fundamental issues of cellular mobile environment maintaining a common set of information. One of the issues is to predict the location of a mobile user whereas the other is to predict the traffic load of each area and accordingly distribute channels among different areas. For location management the entire area covered by cellular architecture is considered as a hierarchy of location areas considering mobile switching centre as the root of the hierarchy and thus a new tree like data structure is introduced. When a call arrives, mobile switching centre computes the location probability of the called mobile unit at all the cells under it with the help of a database and tree-like data structure is kept in mobile switching centre itself. Finally mobile switching centre performs the appropriate searching to find the best probable cell(s) where the desired mobile unit may be traced. The scheme is made more realistic later exploiting the fact that most of the users confine their movement within a group of cells. It is done by making leaf level of the hierarchy dynamic by switching the membership of a cell from one group to the other depending upon the change of probability of finding a user at a cell. For predicting traffic load in each cell, mobile switching centre scans the same database used for predicting the location of a mobile user and finds out frequency of locating the user in each cell. With the help of this information and a heuristic function the cell wise channel requirement is computed. Finally experiments are carried out to see the variation of system cost and delay with time considering call arrival pattern as Poisson distribution and movement pattern by Gaussian distribution.

Published in:

Electrical and Computer Engineering, 2008. ICECE 2008. International Conference on

Date of Conference:

20-22 Dec. 2008

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.