Optimized Dual Low Power Listening for Extending Network's Lifetime in Multi-Hops Wireless Sensor Networks

One of the major sources of energy waste in a Wireless Sensor Network (WSN) is idle listening, i.e., the cost of actively listening for potential packets. This paper focuses on reducing the idle-listening time via a dynamic duty cycling technique which aims at optimizing the sleep interval between consecutive wakeups. We considered dual low power listening (DLPL) WSNs, in which the sender waits a probe signal from the receiver before starting to transmit. Since each sender receives probe signals from several nodes, the data are routed on multiple paths in a cluster-tree network topology. In this context, we propose an optimization framework for minimizing the energy waste of the most power hungry node of the network. To this aims, we first derive an analytic model that predicts the nodes energy consumption. Then, we use the model to derive an iterative algorithm which achieves convergence to a fixed and provably optimum point without employing any central controller. Simulation results via NS-2 simulator are included to illustrate the accuracy of the model, and numerical results assess the validity of the proposed scheme.