Title :
Comparison of Particle Swarm Optimization algorithms in Wireless Sensor Network node localization
Author :
Cen Cao ; Qingjian Ni ; Xushan Yin
Author_Institution :
Sch. of Comput. Sci. & Eng., Southeast Univ., Nanjing, China
Abstract :
The node localization in Wireless Sensor Network (WSN) presently plays an important role in the field of applications. Particle Swarm Optimization (PSO) algorithm is a typical swarm intelligence method. Researchers propose many PSO variants and try to apply PSO algorithm to the related problems in WSN. This paper focuses on the WSN node localization using PSO algorithm. This paper conducts the experiment simulation, comparison and evaluation work in the node localization using PSO algorithm. The performance of different PSO variants with different population topologies is analyzed. Experiment simulations show that WSN node localization using PSO algorithm can get good performance in ring topology and square topology. In particular, the two newly proposed PSO variants (GDPSO and LDPSO) have good performance on this problem. This paper proposes some useful conclusions, which will provide a valuable reference to WSN engineering field.
Keywords :
particle swarm optimisation; swarm intelligence; telecommunication computing; telecommunication network topology; wireless sensor networks; PSO; WSN; node localization; particle swarm optimization; ring topology; square topology; swarm intelligence; wireless sensor network; Heuristic algorithms; Particle swarm optimization; Sociology; Standards; Statistics; Topology; Wireless sensor networks;
Conference_Titel :
Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on
Conference_Location :
San Diego, CA
DOI :
10.1109/SMC.2014.6973916