Energy-efficient framework for data gathering in wireless sensor networks via the combination of sleeping MAC and data aggregation strategies

In this paper, we introduce and evaluate a data collection and transmission paradigm in Wireless Sensor Networks (WSNs), where the primary objective is energy efficiency, while at the same time it is flexible and adaptive to support various Quality of Service (QoS) application constraints. The proposed framework combines two different energy-saving methods, one at the application layer, namely data aggregation, and one at the Medium Access Control (MAC) layer by appropriately adopting sleeping mechanisms. This is achieved by following a cross-layer approach where local information about the status of each sensor, including its sleep/awake schedules, feeds a subsequent data aggregation phase, which gathers correlated data and aggregates it to a single packet towards its way to the sink by applying a fully localised, distributed, probabilistic method. Simulation results demonstrate the significant energy savings achieved by our proposed framework, especially when compared to conventional MAC layer approaches and/or data aggregation approaches.