Data aggregation model using energy-efficient delay scheduling in multi-hop hierarchical wireless sensor networks

This study addresses a data aggregation model in hierarchical sensor networks, which provides centralised and distributed clustering mechanisms with evenly distributed heads. The model includes intra-cluster and inter-cluster network operations, whereas nodes report data and residual energy to a sink. Additionally, an energy merging scheme reduces node´s storage and communication overheads during the collection of node residual energy. The distributed clustering and data reporting with location-based propagation and cluster-based aggregation delay schemes decrease the probability of communication collision, and increase node energy-saving effects. Based on analyses and simulation results, the energy overhead of the model is sensible, given the current state of sensor nodes, and the network lifetime is prolonged with adaptive multi-hop clusters.