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A Novel Light Reflection-Random Walk for Smart Sensors Relocation

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Abstract

This paper presents a new algorithm for relocating sensors in a Wireless Sensor and Robots Network (WSRN) using a mobile robot. The goal is to repair coverage holes using redundant sensors that are caused by an initial random deployment. The holes are repaired without prior knowledge of their positions or that of the redundant sensors. The existing solutions mainly focus either on how to optimally repair holes by determining to where relocate redundant sensors, or how to build a repair path with assumption that the positions of holes and redundant sensors are known. In both scenarios, the literature lacked the optimization of the robot’s path for its initial exploration to identify both the holes and redundant sensors. Our proposed solution introduces an efficient robot trajectory that utilizes stochastic paths that adhere to the principles of light reflection. This trajectory serves the dual purpose of identifying redundant sensors and detecting as well as repairing coverage holes. We achieve this by incorporating the law of large numbers into the light reflection principal, enabling the robot to move randomly while adhering to the pathways of light reflection to efficiently relocate the redundant sensors. This approach results in a highly efficient and effective sensor relocation process. The effectiveness of the proposed solution is assessed across multiple parameters, including relocation time, the length of the relocation path, the robot average moves, and the total energy consumption required to cover holes with varying carrying capacity, dimensions of region of interest, coverage ratio and exit angles of reflection. Through a series of extensive simulations, we provide compelling evidence that our proposed solution distinctly surpasses the existing state-of-the-art approaches. This notable advantage becomes evident in multiple aspects: from reduced relocation time and shorter relocation path length to minimized total energy consumption. These combined enhancements underscore the effectiveness of our solution in tackling the challenge of sensor relocation.

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References

  1. Rajpoot, P., Dwivedi, P.: Optimized and load balanced clustering for wireless sensor networks to increase the lifetime of WSN using MADM approaches. Wireless Netw. 26(1), 215–251 (2020)

    Article  Google Scholar 

  2. Qabouche, H., Sahel, A., Badri, A.: Hybrid energy efficient static routing protocol for homogeneous and heterogeneous large scale WSN. Wireless Netw. 27(1), 575–587 (2021)

    Article  Google Scholar 

  3. Shaimaa, M.M., Haitham, S.H., Saroit, I.A.: Coverage in mobile wireless sensor networks (M-WSN): a survey. Comput. Commun. 110, 133–150 (2017)

    Article  Google Scholar 

  4. Debnath, S., Kumar, A., Hossain, A.: A comprehensive survey of coverage problem and efficient sensor deployment strategies in wireless sensor networks. Indian J. Sci. Technol. 9(45), 1–6 (2016)

    Article  Google Scholar 

  5. Cheng, C.F., Chen, Y.C.: The carrier-based sensor deployment in linear IWSNs with return/non-return branches. IEEE Sens. J. 22(6), 6175–6186 (2022)

    Article  Google Scholar 

  6. Li, X., Fletcher, G., Nayak, A., Stojmenović, I.: Randomized carrier-based sensor relocation in wireless sensor and robot networks. Ad Hoc Netw. 11(7), 1951–1962 (2013)

    Article  Google Scholar 

  7. Kumar, A., Srivastava, R., Kamalasanan, M.N., Mehta, D.S.: Enhancement of light extraction efficiency of organic light emitting diodes using nanostructured indium tin oxide. Opt. Lett. 37(4), 575–577 (2012)

    Article  Google Scholar 

  8. Bambi, C., Brenneman, L., Dauser, T., García, J., Grinberg, V., Ingram, A., Jiang, J., Liu, H., Lohfink, A., Marinucci, A., Mastroserio, G., Middei, R., Nampalliwar, S., Niedźwiecki, A., Steiner, J., Tripathi, A., Zdziarski, A.: Towards precision measurements of accreting black holes using X-ray reflection spectroscopy. Space Sci. Rev. 217(5), 65 (2021)

    Article  Google Scholar 

  9. Zhang, X., Zhou, Y.: Adaptive lighting algorithm experiment. In: 13th IEEE International Conference on Electronic Measurement and Instruments (ICEMI), pp. 348–353. Yangzhou, China (2017)

  10. Petrov, W.W.: On the strong law of large numbers. Stat. Prob. Lett 24(3), 1589–1615 (1996)

    MathSciNet  Google Scholar 

  11. Feng, S., Shi, H., Huang, L., Shen, S., Yu, S., Peng, H., Wu, C.: Unknown hostile environment-oriented autonomous WSN deployment using a mobile robot. J. Netw. Comput. Appl. 182, 053–103 (2021)

    Article  Google Scholar 

  12. Priyadarshi, R., Gupta, B., Anurag, A.: Deployment techniques in wireless sensor networks: a survey, classification, challenges, and future research issues. J. Supercomput. 76(9), 7333–7373 (2020)

    Article  Google Scholar 

  13. Amutha, J., Sharma, S., Nagar, J.: WSN strategies based on sensors, deployment, sensing models, coverage and energy efficiency: review, approaches and open issues. Wireless Pers. Commun. 11(2), 1089–1115 (2020)

    Article  Google Scholar 

  14. Batalin, M.A., Sukhatme, G.S.: The analysis of an efficient algorithm for robot coverage and exploration based on sensor network deployment. In: Proceedings of the 2005 IEEE International Conference on Robotics and Automation, pp. 3478–3485 (2005)

  15. Haotian, L., Barnawi, A., Stojmenovic, I., Wang, C.: Market-based sensor relocation by robot team in wireless sensor networks. Ad-Hoc Sens. Wirel. Netw. 22(3), 259–280 (2014)

    Google Scholar 

  16. Wang, Y., Barnawi, A., Fernandes De Melle, R., Stojmenovic, I.: Localized ant colony of robots for redeployment in wireless sensor networks. Multi-Valued Logic Soft Comput. 23, 35–51 (2014)

    Google Scholar 

  17. Desjardins, B., Falcon, R., Abielmona, R., Petriu, E.: A multi-objective optimization approach to reliable robot-assisted sensor relocation. In: IEEE Congress on Evolutionary Computation (CEC), pp. 56–64 (2015)

  18. Desjardins, B., Falcon, R., Abielmona, R., Petriu, E.: Reliable multiple robot-assisted sensor relocation using multi-objective optimization. In: IEEE Congress on Evolutionary Computation (CEC), pp. 4476–4485 (2016)

  19. Desjardins, B., Falcon, R., Abielmona, R., Petriu, E.: Planning robust sensor relocation trajectories for a mobile robot with evolutionary multi-objective optimization. In: Computational Intelligence in Wireless Sensor Networks, pp. 179–210 (2017)

  20. Falcon, R., Nayak, A., Abielmona, R.: An evolving risk management framework for wireless sensor networks. In: IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA), pp. 1–6 (2011)

  21. Cheng, C., Chen, Y., Lin, J.C.: A carrier-based sensor deployment algorithm for perception layer in the IoT architecture. IEEE Sens. J. 20(17), 10295–10305 (2020)

    Article  Google Scholar 

  22. Belguerche, N., Lasla, N., Benchaiba, M.: On optimal robot displacement for efficient coverage in WSN. In: The 15th International Conference on Advances in Mobile Computing and Multimedia, pp. 175–181 (2017)

  23. Kun, M., Hailan, D., Feng, Q., Ye, D.: A One-Commodity pickup-and-delivery traveling salesman problem solved by a two-stage method : a sensor relocation application. PloS One 14(4), e0215107 (2019)

    Article  Google Scholar 

  24. Parretta, A.: All the light from the Newton’s prism: effects of the multiple internal reflections. Opt. Commun. 474, 126101 (2020)

    Article  Google Scholar 

  25. Xiangyu, M., Yusheng, Z., Jitao, J., Zhipeng, W., Qilong, W.: The optical properties of a visible light filter integrated on the silicon substrate. Opt. Commun. 464, 125510 (2020)

    Article  Google Scholar 

  26. Taylor, R.L., Patterson, R.F., Bozorgnia, A.: Weak laws of large numbers for arrays of Rowes negatively dependent random variables. Appl. Math. Stoch. Anal. 86(5), 804076 (2001)

    Google Scholar 

  27. Carbone, R., Girotti, F., Melchor-Hernandez, A.: On a generalized central limit theorem and large deviations for homogeneous open quantum walks. J. Stat. Phys. 188(1), 8 (2022)

    Article  MathSciNet  Google Scholar 

  28. Horng-Jinh, C., Kuo-Chung, H., Chao-Hsien, W.: Determination of sample size in using central limit theorem for Weibull distribution. Int. J. Inf. Manage. Sci. 17, 31 (2006)

    Google Scholar 

  29. Sakil, C., Benslimane, S.: Relocating redundant sensors in randomly deployed wireless sensor networks. In: IEEE Global Communications Conference (GLOBECOM), pp. 1–6 (2018)

  30. Kusuma, M., Veena, N., Aparna, N.: Effective deployment of sensors in a wireless sensor networks using Hebbian machine learning technique. In: International Conference on Computing, Communication, and Intelligent Systems (ICCCIS), pp. 268–274 (2021)

  31. Biradar, S., Shastry, M.: Redundancy elimination with coverage preserving algorithm in wireless sensor network. Int. J. Commun. Netw. Inf. Secur. (IJCNIS) 10(3), 454 (2018)

    Google Scholar 

  32. El Khamlichi, Y., Mesmoudi, Y., Tahiri, A., Abtoy, A.: A recovery algorithm to detect and repair coverage holes in wireless sensor network system. J. Commun. 13(2), 67–74 (2018)

    Article  Google Scholar 

  33. Feng, X., Zhang, X., Zhang, J., Muhdhar, A.A.: A coverage hole detection and repair algorithm in wireless sensor networks. Cluster Comput. 22(22), 12473–12480 (2019)

    Article  Google Scholar 

  34. Koriem, S.M., Bayoumi, M.A.: Detecting and measuring holes in wireless sensor network. J. King Saud Univ. Comput. Inf. Sci. 32(8), 909–916 (2020)

    Google Scholar 

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Correspondence to Nadia Belguerche.

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Belguerche, N., Belhaouari, S.B., Lasla, N. et al. A Novel Light Reflection-Random Walk for Smart Sensors Relocation. J Netw Syst Manage 32, 7 (2024). https://doi.org/10.1007/s10922-023-09780-x

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