Reliable and Secured Cluster Based Routing in WSN via Lyrebird-Panda Optimization Algorithm

Routing and clustering approaches can assist address the primary issue of dependable energy-aware data transmission in wireless sensor networks (WSN). Data transmission's use in WSN situations has grown recently due to its dynamic nature. However, WSNs face a number of difficulties when sending data, such as a shorter network lifetime, lower EE, and a worse level of security. This study develops a new cluster head selection model for WSN. In this case, a new technique called Red Panda Incorporated Lyrebird Optimization (RPI-LBO) is used to elect the CHs in the best possible way. Energy, link longevity, link quality, security, and trust are all taken into account when performing the CHS. The link lifetime for 100 nodes using RPI-LBO is 42 from the 1200th to the 1800th round. However, the suggested RPI-LBO revealed a longer connection lifetime than the examined LBO, RPA, WaOA, SBOA, and COA schemes for all node counts.