Implementation of the Positioning of an Improved WSN Particle Swarm Optimization in Node Ranging
M.Rambabu Naik1, Shaik Khamuruddeen2, C.Arunabala3, K Siva Naga Narasimgarao4
1Dr. M.Rambabu Naik, Associate Professor, Department of ECE, KKR & KSR Institute Of Technology & Sciences (KITS), Guntur.
2Dr. Shaik Khamuruddeen, Associate Professor, Department of ECE, KKR & KSR Institute Of Technology & Sciences (KITS), Guntur.
3Dr. C. Arunabala, Professor, Department of ECE, KKR & KSR Institute Of Technology & Sciences (KITS), Guntur.
4Mr. K Siva Naga Narasimgarao, Assistant Professor, Department of ECE, KKR & KSR Institute Of Technology & Sciences (KITS), Guntur.
Manuscript received on November 17., 2019. | Revised Manuscript received on November 24 2019. | Manuscript published on 30 November, 2019. | PP: 12677-12781 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7981118419/2019©BEIESP | DOI: 10.35940/ijrte.D7981.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The proposal aims mainly improves the particle swarm optimization of wireless sensor network node positioning in received signal strength intensity (RSSI) ranging. A algorithms is proposed for the existence of local convergence which has significant changes in the effects of convergence speed and stability analysis. It is an algorithm to solve the problem of multiobjective combination optimization, and it is widely used due to less parameters and being easy to be realized. And its basic idea is to compare individuals in the space to particles without quality and volume. The dynamic disturbance factors are introduced to reduce the speed of local convergence and penalty function is introduced, thereby limiting the search range of feasible solutions and avoid consuming time in ineffective solution space.
Keywords: WSN, Dynamic Disturbance Factor, Penalty Function.
Scope of the Article: Foundations Dynamics.