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The IEEE Conference on Local Computer Networks 30th Anniversary (LCN'05)l
A Genetic Algorithm for Finding Optimal Location Area Configurations for Mobility Management
Sydney, Australia
November 15-November 17
ISBN: 0-7695-2421-4
ASCII Text
x 
 
Javid Taheri, Albert Y. Zomaya, "A Genetic Algorithm for Finding Optimal Location Area Configurations for Mobility Management," Local Computer Networks, Annual IEEE Conference on, pp. 568-577, The IEEE Conference on Local Computer Networks 30th Anniversary (LCN'05)l, 2005.
 
 
BibTex
x
 
@article{ 10.1109/LCN.2005.6,
author = {Javid Taheri and Albert Y. Zomaya},
title = {A Genetic Algorithm for Finding Optimal Location Area Configurations for Mobility Management},
journal ={Local Computer Networks, Annual IEEE Conference on},
volume = {0},
year = {2005},
issn = {0742-1303},
pages = {568-577},
doi = {http://doi.ieeecomputersociety.org/10.1109/LCN.2005.6},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Local Computer Networks, Annual IEEE Conference on
TI - A Genetic Algorithm for Finding Optimal Location Area Configurations for Mobility Management
SN - 0742-1303
SP568
EP577
A1 - Javid Taheri,
A1 - Albert Y. Zomaya,
PY - 2005
KW - null
VL - 0
JA - Local Computer Networks, Annual IEEE Conference on
ER -
 
Javid Taheri, The University of Sydney
Albert Y. Zomaya, The University of Sydney

This work presents a new approach to solve the location management problem by using the location areas approach. A modified Genetic Algorithm is used to find the optimal configuration of location areas in a mobile network. The location areas configuration of the network is modeled so that the general condition of all the chromosomes of each population improves rapidly. Since a generic genetic algorithm will not be so efficient in solving this problem, several modifications have been made to the genetic optimizer to improve its performance. These modifications deal with the mutation operation where three types of mutation are considered after the crossover operation of the genetic algorithm. Simulation results are very promising and they lead to network configurations that are unanticipated.

Citation:
Javid Taheri, Albert Y. Zomaya, "A Genetic Algorithm for Finding Optimal Location Area Configurations for Mobility Management," lcn, pp.568-577, The IEEE Conference on Local Computer Networks 30th Anniversary (LCN'05)l, 2005
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