Open AccessAn Improved Intrusion Weed Optimization Algorithm for Node Location in Wireless Sensor Networks
Author(s) -
LI Shi-hui
Publication year - 2022
Publication title -
international journal of circuits, systems and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.156
H-Index - 13
ISSN - 1998-4464
DOI - 10.46300/9106.2022.16.65
Subject(s) - wireless sensor network , computer science , population , operator (biology) , algorithm , node (physics) , chaotic , optimization algorithm , rate of convergence , optimization problem , mathematical optimization , real time computing , computer network , mathematics , engineering , channel (broadcasting) , artificial intelligence , biochemistry , chemistry , demography , structural engineering , repressor , sociology , transcription factor , gene
The distribution optimization of WSN nodes is one of the key issues in WSN research, and also is a research hotspot in the field of communication. Aiming at the distribution optimization of WSN nodes, the distribution optimization scheme of nodes based on improved invasive weed optimization algorithm(IIWO) is proposed. IIWO improves the update strategy of the initial position of weeds by using cubic mapping chaotic operator, and uses the Gauss mutation operator to increase the diversity of the population. The simulation results show that the algorithm proposed in this paper has a higher solution quality and faster convergence speed than IWO and CPSO. In distribution optimization example of WSN nodes, the optimal network coverage rate obtained by IIWO is respectively improved by 1.82% and 0.93% than the IWO and CPSO. Under the condition of obtaining the same network coverage rate, the number of nodes required by IIWO is fewer.