Biologically inspired energy-balanced clustering routing optimization for wireless sensor network

A key challenge in wireless sensor networks (WSNs) is the clustering routing issue, which has been identified as NP-hard. Since the power supply of sensors is limited and the security of network cannot be guaranteed, determining how to optimize a secure clustering routing scheme becomes a significant and challenging task. This paper introduces a novel bio-inspired energy-balanced secure clustering routing (BESCR) algorithm, which can markedly extend network lifespan, vigorously improve security, significantly reduce transmission delay, and maintain balanced energy consumption across nodes. Moreover, a secure clustering routing model based on trust mechanism is introduced, alongside an objective function that considers intra-cluster distance, base station distance, delay, trust value, and node residual energy, making the clustering routing scheme more secure and efficient. What's more, BESCR algorithm incorporates artificial bee colony optimization, chaos generator and genetic mutation operator, which can greatly raise the convergence speed, and reduce the risk of local optima. Simulation results show that BESCR effectively increases the network lifetime, reduces the delay, improves the security, and balances energy costs of nodes.