CRWO: Clustering and routing in wireless sensor networks using optics inspired optimization

In wireless sensor networks (WSNs), cluster head (CH) selection and routing are two well known optimization problems associated with high computational complexity for large scale networks. Optics inspired optimization (OIO) is one of the recent meta-heuristic techniques used to solve a wide range of NP-Hard problems. In this study, firstly an OIO based CH selection algorithm is proposed by considering various parameters such as energy, distance and node degree. Next, clusters are formed using derived potential function. Finally, an OIO based routing algorithm is proposed to compute the route from each CH to the base station (BS) using the same parameters like energy, distance and node degree. In the performance evaluation, the proposed algorithm (CRWO) is extensively tested and compared with some of the existing algorithms based on both conventional and nature inspired routing techniques. Simulation results depict the superiority of the proposed algorithm over its comparatives.