Modeling an Energy Efficient Clustering Protocol with Spider Cat Swarm Optimization for WSN

To run the networks most effectively, the primary activities connected with Wireless Sensor Networks (WSNs), particularly the sensing and communication tasks, must be designed correctly. Because sensor nodes (SN) remain unattended after deployment, their energy (battery supply) and computational capabilities restrict the network's lifespan. The sources of energy must be effectively utilized in order to keep the networks running for a long time. As a result, the WSN's two most important criteria are optimal node location estimate and efficient energy consumption. The Spider Cat Swarm Optimization (SCSO) method is used in this study to optimize the network layout by including it into the load - balancing. The efficiency of the SCSO algorithm-based clustering method is examined in simulation and confirmed in a present experimental. By simulated results, the performance of other treatments based on traditional Modified Low-energy Adaptive Clustering Hierarchy (MODLEACH) and evolutionary method Optimized Swarm Optimization (OPSO) is also investigated and assessed. In compared to MODLEACH and OPSO, the SCSO algorithm based clustering protocol improved system performance (energy consumption).