An adaptive algorithm for compressive approximation of trajectory (AACAT) for delay tolerant networks

Authors:
Rajib Rana;Wen Hu;Tim Wark;Chun Tung Chou
Affiliations:
School of Comp. Sci. and Engineering, University of New South Wales and CSIRO ICT Center, Australia;CSIRO ICT Center, Australia;CSIRO ICT Center, Australia;School of Comp. Sci. and Engineering, University of New South Wales, Australia
Venue:
EWSN'11 Proceedings of the 8th European conference on Wireless sensor networks
Year:
2011

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Abstract

Highly efficient compression provides a promising approach to address the transmission and computation challenges imposed by moving object tracking applications on resource constrained Wireless Sensor Networks (WSNs). In this paper, we propose and design a Compressive Sensing (CS) based trajectory approximation algorithm, Adaptive Algorithm for Compressive Approximation of Trajectory (AACAT), which performs trajectory compression, so as to maximize the information about the trajectory subject to limited bandwidth. Our extensive evaluation using "real" trajectories of three different object groups (animals, pedestrians and vehicles) shows that CS-based trajectory compression reduces up to 30% transmission overheads, for given information loss bounds, compared to the state-of-the-art trajectory compression algorithms. We implement AACAT on the resource-impoverished sensor nodes, which shows that AACAT achieves high compression performance with very limited resource (computation power and energy) overheads.