Next century challenges: scalable coordination in sensor networks
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
Directed diffusion: a scalable and robust communication paradigm for sensor networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
A two-tier data dissemination model for large-scale wireless sensor networks
Proceedings of the 8th annual international conference on Mobile computing and networking
Peer-to-Peer Spatial Queries in Sensor Networks
P2P '03 Proceedings of the 3rd International Conference on Peer-to-Peer Computing
Vineyard Computing: Sensor Networks in Agricultural Production
IEEE Pervasive Computing
A robust data delivery protocol for large scale sensor networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Querying sensor fields by using quadtree based dynamic clusters and task sets
MILCOM'03 Proceedings of the 2003 IEEE conference on Military communications - Volume I
Hierarchical role-based data dissemination in wireless sensor networks
The Journal of Supercomputing
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The envisioned sensor network architecture where some of the nodes may be mobile poses several new challenges to this special type of ad hoc wireless network. Recently, researchers have proposed several data dissemination protocols based on some hierarchical structure mainly constructed by a source node to support mobile sinks. However, such a source-initiated hierarchical structure results in significant resource consumption as the number of source-sink pairs are increased. Additionally, stimulus mobility aggravates the situation, where several sources may build a separate data forwarding hierarchy along the stimulus moving path. In this paper, we propose a new data dissemination protocol that exploits “Quadtree-based network space partitioning” to provide more efficient routing among multiple mobile stimuli and sink nodes. Simulation results show that our work significantly reduces average energy consumption while maintaining comparably higher data delivery ratio.