Taylor political optimizer‐based cluster head selection in IOT‐assisted WSN networks

IoT‐assisted WSN contains various nodes, which are placed on a huge scale that increases complications. Thus, the challenges and issues of these networks fluctuate as compared to WSNs. Hence, sensor nodes are imperative unit that runs on less energy resources. Hence, devising a robust and energy‐effective protocol for increasing network lifetime is a complex task. This paper devises a novel hybrid optimization‐driven approach for selecting cluster head (CH) in IoT‐assisted WSNs. Initially, the simulation of IoT nodes is done by configuration. Thereafter, the Cluster Head selection is done using a newly devised optimization technique, namely the Taylor‐Political optimizer (Taylor‐PO). Thus, fitness is newly developed by adapting certain attributes like energy, delay, inter and intra‐cluster distance, Link Lifetime (LLT), predicted energy, and delay. Here, the multipath routing is accomplished using Tunicate Swarm gray wolf optimization (TSGWO). Thus, the proposed Taylor‐PO is offered for effective Cluster Head selection along with multipath routing using TSGWO. The proposed Taylor‐PO offered improved performance with smallest delay of 0.006 sec, highest energy of 2.368 J, highest throughput of 494.043 kbps.