Optimized Energy-Efficient Routing for IoT Wireless Sensor Networks with Load Balancing using Sparse Autoencoder Capsule Network and Snow Geese Algorithm
Bhuvaneswari M S, N. Balaganesh · 2024
Wireless sensor networks (WSNs) are widely utilized in the Internet of Things (IoT)-based systems to collect data that smart environments require. Load balancing is the most suitable technique to address the issue caused by the energy holes in the network. Therefore, a suitable clustering scheme with load balancing strategy is employed for Energy Efficient (EE) data transmission with less delay and high network lifetime. The load balancing technique reduces the problem of packet loss and prevents the early mortality of nodes that are closer to the gateway. The proposed research work uses Sparse Auto Encoder Capsule Network (SAECN) for inter-cluster and intra-cluster routing in WSN. The network constraints are optimized by employing Snow Geese Algorithm (SGA). The experimental results indicate that the proposed approach achieves a high throughput of 98.5%, packet delivery ratio (PDR) of 99.4%, network lifetime of 265s with less energy consumption of 0.4J and delay of 0.25s which is better than the compared state-of-art approaches.