An immune-swarm intelligence based algorithm for deterministic coverage problems of wireless sensor networks

Autor:	Jun-yu Ao, Shaohua Wang, Bao-lei Wang, Ji-zhong Liu, Q. M. Jonathan Wu
Rok vydání:	2012
Předmět:	Mathematical optimization Artificial immune system Computer science Information sharing Metals and Alloys General Engineering Coverage probability Swarm behaviour Particle swarm optimization Multi-swarm optimization Swarm intelligence Algorithm Wireless sensor network
Zdroj:	Journal of Central South University. 19:3154-3161
ISSN:	2227-5223 2095-2899
Popis:	A novel immune-swarm intelligence (ISI) based algorithm for solving the deterministic coverage problems of wireless sensor networks was presented. It makes full use of information sharing and retains diversity from the principle of particle swarm optimization (PSO) and artificial immune system (AIS). The algorithm was analyzed in detail and proper swarm size, evolving generations, gene-exchange individual order, and gene-exchange proportion in molecule were obtained for better algorithm performances. According to the test results, the appropriate parameters are about 50 swarm individuals, over 3 000 evolving generations, 20%–25% gene-exchange proportion in molecule with gene-exchange taking place between better fitness affinity individuals. The algorithm is practical and effective in maximizing the coverage probability with given number of sensors and minimizing sensor numbers with required coverage probability in sensor placement. It can reach a better result quickly, especially with the proper calculation parameters.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ac0eef15b0af46e2aa3d447f426025c4 https://doi.org/10.1007/s11771-012-1390-x Zobrazit plný text záznamu Full text from SpringerLink