IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
On target tracking with binary proximity sensors
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Distributed and energy-efficient target localization and tracking in wireless sensor networks
Computer Communications
Collaborative signal processing for distributed classification in sensor networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
DCTC: dynamic convoy tree-based collaboration for target tracking in sensor networks
IEEE Transactions on Wireless Communications
Journal of Network and Computer Applications
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Object tracking needs to meet certain real-time and precision constraints, while limited power and storage of sensors issue challenges for it. This paper proposes an energy efficient tracking algorithm (EETA) that reduces energy consumption in sensor network by introducing an event-driven sleep scheduling mechanism. EETAgives tradeoffs between real time and energy efficiency by making a maximum number of sensor nodes outside tracing area stay asleep. EETAreduces the computation complexity on sensors to O(N)by formulating the location predication of an object as a state estimation problem of sensor node, instead of building a complex model of its trajectory.EETAlocates the object using modified weighted centroid algorithm with the complexity of O(N). We evaluate our method with a network of 64 sensor nodes, as well as an analytical probabilistic model. The analytical and experimental results demonstrate the effectiveness of proposed methods.