An approach by adopting multi-objective clustering and data collection along with node sleep scheduling for energy efficient and delay aware WSN

Wireless sensor network (WSN) is composed of high density spatially dispersed and dedicated autonomous sensors for monitoring or recording the physical conditions of the environment. Still, the sensor nodes are battery-powered with limited energy supply; moreover, in many of the applications, sensor nodes are deployed in harsh natural environment or vast space so that the continuous energy supplement is impossible. Many authors focused to achieve trade-offs in terms of energy, and delay for such data collection tasks; few of them are concerned with sleep scheduling. In this paper, we propose energy efficient and delay aware routing using multi-objective clustering and a sleep schedules scheme for WSN ((EDR)-D-2-MCS). The first contribution of this paper is to propose a multi-objective wolf optimization algorithm for clustering. Additionally, a sleep scheduling scheme is utilized to save power and increase the lifetime of the entire network. The second contribution is that the efficient data collection is achieved by a selective track search algorithm, which provides a suitable path between the source-destination pairs. The simulation results show that (EDR)-D-2-MCS approach greatly contributes to minimizing energy consumption, delay, and overhead; maximize the network lifetime and delivery ratio.