Optimization Techniques for IoT using Adaptive Clustering

In several fields of networking, like precision agriculture, the internet of things, and so on, the quest for wireless sensor networks increases daily. The vision of the internet of things can be achieved with the help of Wireless Sensor Network; it introduces a virtual layer which enables a computer system to read data from the physical world. Cluster-based routing schemes decrease energy consumption and increase data aggregation efficiency. Genetic Algorithm is therefore one of the optimization strategies that can be used to choose a better cluster head without compromising the network's lifetime provided that better clustering parameters are used to create fitness function to curtail energy consumption in the network. In the same vein, the Genetic Algorithm is often used to select cluster heads that constitute the paths to relay the data from the source to the destination i.e., to optimize the path. In this paper, a Genetic Algorithm based-adaptive clustering using the Mobile Low Energy Adaptive Clustering Hierarchy (Mobile LEACH) protocol is proposed. In many proposed works, the Genetic Algorithm is employed to elect the cluster head using better fitness parameters. Genetic Algorithm has been used to optimize LEACH protocol in many previous works, but few have considered Mobile LEACH. The proposed work targets to increase the lifespan of the network by reducing the energy consumed in the data transmission process.