Secure clustering and routing – based adaptive – bald eagle search for wireless sensor networks

Abstract

Wireless sensor networks (WSNs) are self-regulating networks consisting of several tiny sensor nodes for monitoring and tracking applications over extensive areas. Energy consumption and security are the two significant challenges in these networks due to their limited resources and open nature. To address these challenges and optimize energy consumption while ensuring security, this research proposes an adaptive – bald eagle search (A-BES) optimization algorithm enabled secure clustering and routing for WSNs. The A-BES algorithm selects secure cluster heads (SCHs) through several fitness functions, thereby reducing energy consumption across the nodes. Next, secure and optimal routes are chosen using A-BES to prevent malicious nodes from interfering with the communication paths and to enhance the overall network lifetime. The proposed algorithm shows significantly lower energy consumption, with values of 0.27, 0.81, 1.38, 2.27, and 3.01 J as the number of nodes increases from 100 to 300. This demonstrates a clear improvement over the existing residual energy-based data availability approach (REDAA).