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Approximate event detection over multi-modal sensing data

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Abstract

Composite event detection is one of the fundamental tasks for heterogeneous wireless sensor networks (WSNs). Multi-modal data generated by heterogeneous sensors bring new challenges for composite event monitoring in heterogeneous WSNs. By exploiting the correlations between different types of data, the approximate composite event detection problem is investigated in this paper. The optimal transmitting scheme problem is proposed to calculate the optimal transmitting scheme with minimum cost on the constraint that the confidence of the composite event must exceed the threshold. The optimal transmitting scheme problem is proved to belong to NP-complete. A dynamic programming based algorithm is presented for simple linear confidence combination operators, which runs in pseudo-polynomial time. The greedy based approximate algorithm is also designed for general confidence combination operators and the approximate ratio is proved to be 2 for “+” as the confidence combination operator. The simulation results show that our algorithms can reduce energy consumption significantly.

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Acknowledgments

This work was supported in part by the National Grand Fundamental Research Program of China (973 Program) under Grant No. 2012CB316200, the National Natural Science Foundation of China (NSFC) under Grant No. 61190115, No. 61033015 and No. 61370217

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Authors and Affiliations

  1. Department of Computer Science and Technology, Harbin Institute of Technology, 90 West Dazhi Street, PO Box 750, Harbin, China

    Jing Gao & Jianzhong Li

  2. Department of Computer Science, Georgia State University, 25 Park Place, Suite 749, Atlanta, GA, 30303, USA

    Yingshu Li

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  1. Jing Gao
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  2. Jianzhong Li
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  3. Yingshu Li
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Correspondence to Jing Gao.

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Gao, J., Li, J. & Li, Y. Approximate event detection over multi-modal sensing data. J Comb Optim 32, 1002–1016 (2016). https://doi.org/10.1007/s10878-015-9847-0

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