Spatial correlation aware protocols for efficient data aggregation of moving object in wireless sensor networks

In wireless sensor networks (wsns), power consumption of sensor nodes is the mainconstraint. emerging in-network aggregation techniques are increasingly being sought after to addressthis key challenge and to save precious energy. one application of wsns is in data gathering of movingobjects. in order to achieve complete coverage, this type of application requires spatially dense sensordeployment, which, under close observation, exhibits important spatial correlation characteristics. therate distortion (rd) theory is a data aggregation technique that can take advantage of this type ofcorrelation with the help of a cluster based communication model. due to object movement, therate-distortion based aggregation incurs high computation overhead. this paper first introduces anintroduction for the rate-distortion based moving object data aggregation model. then, to overcome thehigh computation overhead, several low overhead protocols are proposed based on this model, namely,a static cluster-based protocol that uses static clustering, a dynamic cluster-based protocol that usesdynamic clustering, and a hybrid protocol which takes advantage of the other two protocols. simulationresults show that with the hybrid method, it is possible to save more than 36% of the nodes' energy whencompared to the other approaches.