The impact of spatial correlation on routing with compression in wireless sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Spatio-temporal correlation: theory and applications for wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: In memroy of Olga Casals
Efficient gathering of correlated data in sensor networks
Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing
On the optimal density for real-time data gathering of spatio-temporal processes in sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Spatial correlation-based collaborative medium access control in wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
Modeling spatially correlated data in sensor networks
ACM Transactions on Sensor Networks (TOSN)
On Computing Mobile Agent Routes for Data Fusion in Distributed Sensor Networks
IEEE Transactions on Knowledge and Data Engineering
Power, spatio-temporal bandwidth, and distortion in large sensor networks
IEEE Journal on Selected Areas in Communications
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Wireless Sensor Networks (WSN) are mainly characterized by dense deployment of sensor nodes. Due to the spatial correlation between sensor nodes and constrained resources of nodes, Spatial Correlation-based Mobile Agent Routing (SCMAR) algorithm is proposed to exploit such correlation for the realization of advanced efficient Mobile Agent routing protocol in order to estimate the event with energy efficient way. The theoretical framework of SCMAR is developed to suppress redundancy information collection under a distortion constraint for reducing the energy consumption without compromising the estimated reliability achieved at the sink. Finally, Simulation results show that SCMAR achieves better performance than existing Mobile Agent Routes for Data Fusion (MARDF) routing algorithm from perspectives of energy consumption in a variety of correlated data gathering applications.