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An approach to solve the target coverage problem by efficient deployment and scheduling of sensor nodes in WSN

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Abstract

Network lifetime play a vital role in setting up an energy efficient wireless sensor network. The lifetime of the network can be improved by efficient deployment and scheduling of the sensor nodes inside the network. In this paper, on the basis of mathematically calculated upper bound lifetime of the network, the sensor nodes are efficiently deployed by using Simulated Annealing and Particle Swarm Optimization with pre-specified sensing range of the sensor nodes and on the second fold the sensor nodes are efficiently scheduled by applying the Simulated Annealing and Dempster Shafer Theory. The overall objective of this paper is to find the optimized location and schedule for sensor nodes. The comparative study shows that the simulated annealing and particle swarm optimization algorithms performs better for sensors deployment. Simulated annealing and Dempster Shafer theory achieves the goal to provide the different schedules with high efficiency.

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References

  • Bai X, Kumar S, Xuan D, Yun Z, Lai TH (2006) Deploying wireless sensors to achieve both coverage and connectivity. In: Proceedings of 7th ACM international symposium on mobile ad hoc networking and Computing, pp 131–142

  • Bai X, Yun Z, Xuan D, Lai T, Jia W (2010) Optimal patterns for four-connectivity and full coverage in wireless sensor networks. IEEE Trans Mobile Comput 9(3):435–448

    Article  Google Scholar 

  • Chang C-Y, Chang H-R (2008) Energy-aware node placement, topology control and MAC scheduling for wireless sensor networks. Comput Netw 52:2189–2204

    Article  MATH  Google Scholar 

  • Cheng Z, Perillo M, Heinzelman W (2008) General network lifetime and cost models for evaluating sensor network deployment strategies. IEEE Trans Mobile Comput 7(4):484–497

    Article  Google Scholar 

  • Chong C-Y, Kumar S (2003) Sensor networks: evolution, opportunities, and challenges. Proc IEEE 91:1247–1256

    Article  Google Scholar 

  • Dempster AP (1968) A generalization of bayesian inference. J R Stat Soc Ser B 30:205–247

    MathSciNet  MATH  Google Scholar 

  • Eberhart R, Kennedy J (1995) A new optimizer using particle swarm theory. In: Proceedings of 6th international symposium on micro machine and human science, pp 39–43

  • Huang C-F, Tseng Y-C (2003) The coverage problem in a wireless sensor network. In: Proceedings of 2nd ACM international conference on wireless sensor network applications, pp 115–121

  • Kennedy J, Eberhart R (1995) Particle swarm optimization. Proc IEEE Int Conf Neural Netw 4:1942–1948

    Article  Google Scholar 

  • Keshavarzian A, Lee H, Venkatraman L (2006) Wakeup scheduling in wireless sensor networks. In: Proceedings of 7th ACM international symposium mobile ad hoc networking and computing, pp 322–333

  • Kirkpatrick S, GelattJr CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220(4598):671–680

    Article  MathSciNet  MATH  Google Scholar 

  • Li Y, Gao S (2008) Designing k-coverage schedules in wireless sensor networks. J Combinat Opt 15(2):127–146

    Article  MathSciNet  MATH  Google Scholar 

  • Liu C, Wu K, King V (2005) Randomized coverage-preserving scheduling schemes for wireless sensor networks. In: Proceedings of Networking, pp 956–967

  • Mini S, Udgata SK, Sabat SL (2011) A heuristic to maximize network lifetime for target coverage problem in wireless sensor networks. AdHoc Sensor Wireless Netw 13(3–4):251–269

    Google Scholar 

  • Onur E, Ersoy C, Deliç H (2005) Quality of deployment in surveillance wireless sensor networks. Int J Wireless Inform Netw 12(1):61–67

    Article  Google Scholar 

  • Ozturk C, Karaboga D, Gorkemli B (2011) Probabilistic dynamic deployment of wireless sensor networks by artificial bee colony algorithm. Sensors 11(6):6056–6065

    Article  Google Scholar 

  • Makhoul A, Pham, C (2009) Dynamic scheduling of cover-sets in randomly deployed wireless video sensor networks for surveillance applications. In: Proceedings of 2nd IFIP conference on wireless days, pp 73–78

  • Shafer, G (1976) A mathematical theory of evidence. Princeton University Press. ISBN 0-608-02508-9

  • Udgata SK, Sabat SL, Mini S (2009) Sensor deployment in irregular terrain using artificial bee colony algorithm. In: Proceedings of world congress on nature and biologically inspired computing, pp 1309–1314

  • Wang J, Ghosh R, Das S (2010) A survey on sensor localization. J Control Theory Appl 8(1):2–11

    Article  MATH  Google Scholar 

  • Yen L-H, Cheng Y-M (2009) Range-based sleep scheduling (RBSS) for wireless sensor networks. Wireless Pers Commun 48:411–423

    Article  Google Scholar 

  • Yun Z, Bai X, Xuan D, Lai T, Jia W (2010) Optimal deployment patterns for full coverage and k-connectivity (k ≤ 6) wireless sensor networks. IEEE ACM Trans Netw 18(3):934–947

    Article  Google Scholar 

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Correspondence to Devesh Pratap Singh.

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Singh, D.P., Pant, B. An approach to solve the target coverage problem by efficient deployment and scheduling of sensor nodes in WSN. Int J Syst Assur Eng Manag 8, 493–514 (2017). https://doi.org/10.1007/s13198-016-0457-8

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  • DOI: https://doi.org/10.1007/s13198-016-0457-8

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