Accurate, dynamic, and distributed localization of phenomena for mobile sensor networks

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Anagnostopoulos, Christos ; Hadjiefthymiades, Stathes ; Kolomvatsos, Kostas (2016)

We present a robust, dynamic scheme for the automatic self-deployment and relocation of mobile sensor\ud nodes (e.g., unmanned ground vehicles, robots) around areas where phenomena take place. Our scheme aims\ud (i) to sense environmental contextual parameters and accurately capture the spatio-temporal evolution of a\ud certain phenomenon (e.g., fire, air contamination) and (ii) to fully automate the deployment process by letting\ud nodes relocate, self-organize (and self-reorganize) and optimally cover the focus area. Our intention is to\ud ‘opportunistically’ modify the previous placement of nodes to attain high quality phenomena monitoring. The\ud required intelligence is fully distributed within the mobile sensor network so that the deployment algorithm\ud is executed incrementally by different nodes. The presented algorithm adopts the Particle Swarm Optimization\ud technique, which yields very promising results as reported in the paper (performance assessment). Our\ud findings show that the proposed algorithm captures a certain phenomenon with very high accuracy while\ud maintaining the network-wide energy expenditure at low levels. Random occurrences of similar phenomena\ud put stress upon the algorithm which manages to react promptly and efficiently manage the available sensing\ud resources in the broader setting.
  • References (90)
    90 references, page 1 of 9

    Akcan, H., Kriakov, V., Bronnimann, H., Delis, A., 'Managing Cohort Movement of Mobile Sensors via GPSfree & Compass-free Node Localization', Journal of Parallel and Distributed Computing, 70(7): 743-757, 2010.

    Anagnostopoulos, C., Hadjiefthymiades, S., 'Enhancing Situation-Aware Systems through Imprecise Reasoning', IEEE Transactions on Mobile Computing, 7(10):1153-1168, Oct. 2008

    Averill M. L., David Kelton, W., 'Simulation Modeling and Analysis', 3rd, McGraw-Hill, 0070592926, 2000.

    Azlina, N., Aziz, A., Mohemmed, A. W., Zhang, M., 'Particle Swarm Optimization for Coverage Maximization and Energy Conservation in Wireless Sensor Networks', LNCS 6025, pp. 51-60, Applications of Evolutionary Computation, 2010.

    Bai, X., Xuan, D., Yun, Z., Lai, T. H., Jia, W., 'Complete optimal deployment patterns for full-coverage and k-connectivity (k 6) wireless sensor networks', 9th ACM MobiHoc08, pp.401-410, 2008.

    Bartolini N., Calamoneri T., Fusco E., Massini A., Silvestri S., 'Snap and Spread: A Self-deployment Algorithm for Mobile Sensor Networks', Distributed Computing in Sensor Systems, LNCS 5067, pp. 451- 456, 2008.

    Bulusu, N., Heidemann, J., Estrin, D., Tran, T., 'Self-configuring localization systems: Design and experimental evaluation', ACM Trans. Embed. Comput. Syst. 2004, 3, 24-60.

    Cai, X., Cui, Y., Tan, Y., 'Predicted modified PSO with time-varying Accelerator coefficients', Int. J. of BioInspired Computation, 1(1/2):50-60, 2009.

    Chakrabarty, K., Iyengar, S., Qi, H., Cho, E., 'Coding theory framework for target location in distributed sensor networks', In Proc. International Symposium on Information Technology: Coding and Computing, pp.130-134, 2001.

    Chakrabarty, K., Iyengar, S., Qi, H., Cho, E., 'Grid coverage for surveillance and target location in distributed sensor networks', IEEE Trans. Comput. 51(12):1448-1453, 2002.

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