DocumentCode
2669436
Title
Optimal location management in mobile computing with hybrid genetic algorithm and particle swarm optimization (GA-PSO)
Author
Wang, Lipo ; Si, Guanglin
Author_Institution
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
fYear
2010
fDate
12-15 Dec. 2010
Firstpage
1160
Lastpage
1163
Abstract
Location management is an important and complex issue in mobile computing. In the reporting cell location management scheme, the concept of reporting cell was introduced to simplify the management process. As a result, there is a need to optimize the allocation design of reporting cells, since it determines the overall location management cost. We present an approach based on particle swarm optimization (PSO) to obtain minimum cost in the location management problem. Genetic algorithms (GA) are used to improve PSO. Simulation results show that the hybrid algorithm can locate the optimal solution in most cases, within a shorter computational time compared with other algorithms.
Keywords
genetic algorithms; mobile computing; particle swarm optimisation; GA-PSO; cell location management; hybrid genetic algorithm and particle swarm optimization; mobile computing; optimal location management; Gallium; genetic algorithm; location management; mobile computing; particle swarm optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronics, Circuits, and Systems (ICECS), 2010 17th IEEE International Conference on
Conference_Location
Athens
Print_ISBN
978-1-4244-8155-2
Type
conf
DOI
10.1109/ICECS.2010.5724723
Filename
5724723
Link To Document