Energy-Aware Wake-up Scheduling for Data Collection and Aggregation

A sensor in wireless sensor networks (WSNs) periodically produces data as it monitors its vicinity. The basic operation in such a network is the systematic gathering (with or without in-network aggregation) and transmitting of sensed data to a base station for further processing. A key challenging question in WSNs is to schedule nodes’ activities to reduce energy consumption. In this paper, we focus on designing energy efficient protocols for low-data-rate WSNs, where sensors consume different energy in different radio states (transmitting, receiving, listening, sleeping, and being idle) and also consume energy for state-transition. We design both centralized and distributed energy efficient and interference-aware algorithms for homogeneous networks and heterogeneous networks. We use TDMA as the MAC layer protocol and schedule the sensor nodes with consecutive timeslots at different radio states while reducing the number of state transitions. We prove that the energy consumption by our scheduling for homogeneous network is at most a constant times that of the optimum and the energy consumption by our scheduling for heterogeneous network is at most Θ(log Rmax Rmin ) times of the optimum. We also propose efficient algorithms to construct data gathering tree such that the energy consumption and the network throughput is within a constant factor of the optimum. Extensive simulation studies show that our algorithms do reduce considerable energy consumption.