Implementation of PSO in Wireless Sensor Network
Wireless sensor networks have several sensors compatible with a limited capacity battery. The network hierarchy can be selected according to the required applications, such as bulk order. Group leaders play a key role in the assembly of a wireless sensor network. Particle Swarm Improvement (PSO) is a swarm-based intelligence method to identify the best solution by flock behavior. PSO is based on the movement and intelligence of swarms. The social learning factor can achieve a better convergence speed and the particle redefinition mechanism reduces the chances of falling to the local maximum. Optimization is a mathematical technique used to know the maximum or minimum functions in some possible areas. A variety of optimization techniques are involved in the best solutions. Particle Swarm Optimization (PSO) is a relatively recent, topical and robust optimization method that is widely used to detect a global optimal solution within a complex search space. The proposed approach can give the best results as demonstrated in the simulation results.
"Implementation of PSO in Wireless Sensor Network ", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.4, Issue 8, page no.278 - 283, August-2019, Available :https://ijsdr.org/papers/IJSDR1908045.pdf
Volume 4
Issue 8,
August-2019
Pages : 278 - 283
Paper Reg. ID: IJSDR_190918
Published Paper Id: IJSDR1908045
Downloads: 000347245
Research Area: Engineering
Country: -, -, -
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
