Title :
Extending the lifetime of dynamic wireless sensor networks by genetic algorithm
Author :
Liao, Chien-Chih ; Ting, Chuan-Kang
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Chung Cheng Univ., Chiayi, Taiwan
Abstract :
Lifetime is a critical issue at wireless sensor networks (WSNs). Partitioning the set of sensors into several covers over all targets and enabling the covers by turns can effectively extend the lifetime. The problem formulation regarding optimization of sensor partition commonly assumes static networks; however, the composition and topology of real-world WSNs can vary with time due to hardware failure or communication error. This study considers extending the lifetime of dynamic WSNs; specifically, some sensors may fail or recover during the lifetime. In addition, we propose two genetic algorithms (GAs) to deal with this dynamic optimization problem. A series of simulations was conducted to examine the performance of the proposed algorithms. The simulation results validate the effectiveness of the GAs on extending the lifetime under dynamic network environment.
Keywords :
dynamic programming; genetic algorithms; wireless sensor networks; GA; communication error; dynamic WSN; dynamic optimization problem; dynamic wireless sensor networks; genetic algorithms; hardware failure; real-world WSN topology; sensor partition optimization; static networks; Biological cells; Genetic algorithms; Heuristic algorithms; Optimization; Sensors; Upper bound; Wireless sensor networks; Dynamic Optimization; Genetic Algorithm; Lifetime; Set K-Cover Problem; Wireless Sensor Network;
Conference_Titel :
Evolutionary Computation (CEC), 2012 IEEE Congress on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1510-4
Electronic_ISBN :
978-1-4673-1508-1
DOI :
10.1109/CEC.2012.6252860