Skip to main content
Log in

Modeling and Analysis of Grid-Based Target Searching Problems in a Mobile Sensor Network

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

An Erratum to this article was published on 12 September 2017

This article has been updated

Abstract

Target searching is one of the challenging research areas which finds applications in many critical real-time scenarios. The modeling and analysis play a vital role to solve real-time problems. This paper addresses a number of grid-based target searching problems in a single searcher-single target environment applicable to real-time scenarios and various approaches are introduced for modeling and analyzing the problems. The solutions derived from the proposed approaches facilitate the understanding of the problems in detail. We have initially, modeled and analyzed the problems as an extensive-form game and a normal-form game, by deducing appropriate strategies for the respective players (searcher and target) along with expected payoffs. In the paper, a mobile sensor and a mobile object play the role of a searcher and a target, respectively. Later, the problem is viewed from a different dimension by representing it as a state transition diagram and a finite automaton to highlight the differences resulting from varying activities of the searcher and the target. This is further extended to key-based target searching with an aim to minimize the search time. In this paper, we have highlighted few real-time target searching problems similar to the identified problems in the conclusion.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Change history

  • 12 September 2017

    An erratum to this article has been published.

References

  1. Shen, S., Yue, G., & Cao, Q. (2011). A survey of game theory in wireless sensor networks security. Journal of Networks, 6(3), 521–532.

    Article  Google Scholar 

  2. Shi, H. Y., Wang, W. L., Kwok, N. M., & Chen, S. Y. (2012). Game theory for wireless sensor networks: A survey. Sensors, 12(7), 9055–9097.

    Article  Google Scholar 

  3. Machado, R., & Tekinay, S. (2008). A survey of game-theoretic approaches in wireless sensor networks. Computer Networks (Elsevier), 52, 3047–3061.

    Article  MATH  Google Scholar 

  4. Berger, J., Lo, N., & Noel, M. (2014). A new multi-target, multi-agent search-and-rescue path planning approach. International Journal of Computer, Electrical, Automation, Control and Information Engineering, 8(6), 935–944.

    Google Scholar 

  5. Nussbaum, D., & Yörükcü, A. (2015). Moving target search with subgoal graphs. In 8th International symposium on combinatorial search (SoCS).

  6. Ramos, H. S., Boukerche, A., Pazzi, R. W., Frery, A. C., & Loureiro, A. A. F. (2012). Cooperative target tracking in vehicular sensor networks. IEEE Wireless Communications, 19(5), 66–73.

    Article  Google Scholar 

  7. Zhu, Y., Vikram, A., Fu, H., & Guan, Y. (2014). On non-cooperative multiple-target tracking with wireless sensor networks. IEEE Transactions on Wireless Communications, 13(11), 6496–6510.

    Article  Google Scholar 

  8. Yan, D., Wang, J., Liu, L., & Song, A. (2008). Target tracking based on multiagent and game theory in wireless sensor network. In 11th IEEE international conference (ICCT) (pp. 97–100).

  9. Van, D., Wang, J., Liu, L., & Gao, J. (2008). Target tracking based on cluster and game theory in wireless sensor network. In 2nd IET international conference (ICWMMN) (pp. 45–48).

  10. Jiang, C., Dong, G., & Wang, B. (2005). Detection and tracking of region-based evolving targets in sensor networks. In IEEE international conference (ICCCN) (pp. 563–568).

  11. Meng, Y. (2008). Multi-robot searching using game-theory based approach. International Journal Advanced Robotic Systems, 5(4), 341–350.

    Article  Google Scholar 

  12. Das, T., & Roy, S. (2014). Game theory inspired mobile object trapping system in mobile wireless sensor network. In IEEE international conference (ICESC) (pp. 245–250).

  13. Antoniades, A., Kim, H. J., & Sastry, S. (2003). Pursuit-evasion strategies for teams of multiple agents with incomplete information. In 42nd IEEE conference (ICDC) (Vol. 1, pp. 756–761).

  14. Chung, T. H., & Burdick, J. W. (2008). Multi-agent probabilistic search in a sequential decision-theoretic framework. In IEEE international conference (ICRA) (pp. 146–151).

  15. Renzaglia, A., Noori, N., & Isler, V. (2014). The role of target modeling in designing search strategies. IEEE (IROS), 4260–4265.

  16. Waharte, S., Symington, A., & Trigoni, N. (2010). Probabilistic search with agile UAVs. In IEEE international conference (ICRA) (pp. 2840–2845).

  17. Isler, V., Kannan, S., & Khanna, S. (2005). Randomized pursuit-evasion in a polygonal environment. IEEE Transactions on Robototics, 21(5), 875–884.

    Article  MATH  Google Scholar 

  18. Khan, A., Yanmaz, E., & Rinner, B. (2014). Information merging in multi-UAV cooperative search. In IEEE international conference (ICRA) (pp. 3122–3129).

  19. Bhattacharyya, C. K., & Bhattacharyya, S. (2008). Detecting re-entry of a moving object in an irregular space. In 3rd International conference on sensing technology.

  20. Nieberg, S. M., Kropat, E., Pickl, S., & Bordetsky, A. (2013). Intercepting a target with sensor swarms. In IEEE international conference (HICSS) (pp. 1222–1230).

  21. Maxwell, P., Maciejewski, A. A., Siegel, H. J., Potter, J., & Smith, J. (2009). A mathematical model of robust military village searches for decision making purposes. In International conference on information and knowledge engineering (IKE 09) (pp. 311–316).

  22. Cox, J. S., & Durfee, E. H. (2005). An efficient algorithm for multiagent plan coordination. In International joint conference on autonomous agents and multiagent systems.

  23. Strode, C. (2011). Optimising multistatic sensor locations using path planning and game theory. In IEEE symposium (CISDA) (pp. 9–16).

  24. Nowak, M. A., & Sigmund, K. (2000). Games on grids. In U. Dieckmann, R. Law, & J. A. J. Metz (Eds.), The geometry of ecological interactions: Simplifying spatial complexity (pp. 135–150). Cambridge: Cambridge University Press.

    Chapter  Google Scholar 

  25. Malvone, V., Murano, A., & Sorrentino, L. (2015). Games with additional winning strategies. In CILC’15, CEUR workshop proceedings (pp. 175–180).

  26. Romero, J. (2011). Finite automata in undiscounted repeated games with private monitoring. Purdue University, Department of Economics, Purdue University Economics.

  27. Bertrand, N., Genest, B., & Gimbert, H. (2009). Qualitative determinacy and decidability of stochastic games with signals. In Proceedings of LICS: Logic in computer science (319–328). IEEE Computer Society.

  28. Chatterjee, K., & Doyen, L. (2012). Partial-observation stochastic games: How to win when belief fails. In Proceedingsof LICS (pp. 175–184). IEEE Computer Society Press.

  29. Marks, R. (1992). Repeated games and finite automata. In J. Creedy, J. Borland, & J. Eichberger (Eds.), Recent developments in game theory (Chap. 2, pp. 43–64). London: Edward Elgar Publishing Limited.

  30. Gal, S. (1979). Search games with mobile and immobile hider. SIAM Journal on Control and Optimization, 17(1), 99–122.

    Article  MathSciNet  MATH  Google Scholar 

  31. Adler, M., Räcke, H., Sivadasan, N., Sohler, C., & Vöcking, B. (2002). Randomized pursuit-evasion in graphs. In ICALP (pp. 901–912).

  32. Isler, V., Kannan, S., & Khanna, S. (2004). Randomized pursuit-evasion with limited visibility. In Proceedings of ACM-SIAM symposium on discrete algorithms-SODA (pp. 1053–1063).

  33. Hazra, T., Nene, M., & Kumar, C. R. S. (2016). Optimal strategies for searching a mobile object using mobile sensors in a grid environment. In IEEE international conference (ICACCS).

  34. Hazra, T., Nene, M., & Kumar, C. R. S. (2017). A strategic framework for searching mobile targets using mobile sensors. Wireless Personal Communications. doi:10.1007/s11277-017-4113-7.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tanmoy Hazra.

Additional information

An erratum to this article is available at https://doi.org/10.1007/s11277-017-4930-8.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hazra, T., Kumar, C.R.S. & Nene, M.J. Modeling and Analysis of Grid-Based Target Searching Problems in a Mobile Sensor Network. Wireless Pers Commun 95, 4717–4732 (2017). https://doi.org/10.1007/s11277-017-4115-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-017-4115-5

Keywords

Navigation