A novel cluster head selection scheme based on BCO for Internet of Things

The Internet of Things (IoT) has attracted the attention of researchers and is still undergoing progress as a result of the growing use of smart service and devices. The IoT networks challenge numerous problems that need to be fixed. The key problem is how to decrease energy usage while extending network lifetime. Clustering is the energy-efficient data transmission technique that uses the least amount of energy while simultaneously extending the network's life. In this research work, a bacterial colony optimization (BCO-C) approach is used to select the best CH for the LEACH-C. The suggested novel energy-efficient algorithm enhances the behavior of global search and provides appropriate CH positioning. The residual energy, number of alive nodes, and throughput are used to analyze the performance of the developed algorithm. The simulation findings demonstrate an increase in network lifespan, which raises the number of active nodes and lowers energy consumption.