Towards Efficient Sensor Placement for Industrial Wireless Sensor Network

Authors

  • Pavithra Ravikumar Research Scholar Department of Mathematics Anna University CEG Campus
  • D Arivudainambi Professor Department of Mathematics Anna University CEG Campus

DOI:

https://doi.org/10.26555/jiteki.v6i2.19134

Keywords:

Industrial Wireless Sensor Networks, Vertex Coloring, Optimal Sensor Placement, Green Computing, Sequential vertex coloring, Sensor requirement

Abstract

Industrial Wireless Sensor Network (IWSN) is the recent emergence in wireless technologies that facilitate industrial applications. IWSN constructs a reliable and self-responding industrial system using interconnected intelligent sensors. These sensors continuously monitor and analyze the industrial process to evoke its best performance. Since the sensors are resource-constrained and communicate wirelessly, the excess sensor placement utilizes more energy and also affects the environment. Thus, sensors need to use efficiently to minimize their network traffic and energy utilization. In this paper, we proposed a vertex coloring based optimal sensor placement to determine the minimal sensor requirement for an efficient network.

References

Astorino, A., Gaudioso, M., and Miglionico, G., “Lagrangian relaxation for the directional sensor coverage problem with continuous orientationâ€, Omega, Vol. 75, pp. 77-86, 2018. DOI: https://doi.org/10.1016/j.omega.2017.03.001

Choudhuri, R., and Das RK., “Coverage of targets in mobile sensor networks with restricted mobilityâ€, IEEE Access, vol. 6, pp. 10803-10813, 2018. DOI: https://doi.org/10.1109/ACCESS.2018.2801941

Craparo, E. M., Fugenschuh, A., Hof, C., and Karatas, M., “Optimizing source and receiver placement in multi-static sonar networks to monitor fixed targetsâ€, European Journal of Operational Research, vol. 272, no. 3, pp. 816-831, 2019. DOI: https://doi.org/10.1016/j.ejor.2018.02.006

Goyal, S., and Patterh, M. S., “Wireless sensor network localization based on cuckoo search algorithmâ€, Wireless Personal Communications, vol. 79, no. 1, pp. 223-234, 2014. DOI: https://doi.org/10.1007/s11277-014-1850-8

Gungor V. C., and Hancke, G. P., “Industrial wireless sensor networks: Challenges, design principles, and technical approaches,†IEEE Transactions on industrial electronics, vol. 56, no. 10, pp. 4258-4265, 2009. DOI: https://doi.org/10.1109/TIE.2009.2015754

Guo, J., and Jafarkhani, H., “Movement-efficient sensor deployment in wireless sensor networkâ€, IEEE International Conference on Communications, pp. 1-6, 2018. DOI: https://doi.org/10.1109/ICC.2018.8422124

Guo, X., Zhao, C., Yang, X., and Sun, C., â€A deterministic sensor node deployment method with target coverage and node connectivity,†Artificial Intelligence and Computational Intelligence, vol. 7, no. 3, pp. 201-207, 2011. DOI: https://doi.org/10.1007/978-3-642-23887-1_25

Gupta, G. P., and Jha, S., “Biogeography-based optimization scheme for solving the coverage and connected node placement problem for wireless sensor networksâ€, Wireless Networks, vol. 25, no. 6, pp. 3167-3177, 2019. DOI: https://doi.org/10.1007/s11276-018-1709-0

Harizan, S., and Kuila, P., “Coverage and connectivity aware energy efficient scheduling in target based wireless sensor networks: an improved genetic algorithm based approachâ€, Wireless Networks, Vol. 25, no. 4, pp. 1995-2011, 2019. DOI: https://doi.org/10.1007/s11276-018-1792-2

Huang, J., Meng, Y., Gong, X., Liu, Y., and Duan, Q., “A novel deployment scheme for green internet of thingsâ€, IEEE Internet of Things Journal, vol. 1, no. 2, pp. 196-205, 2014. DOI: https://doi.org/10.1109/JIOT.2014.2301819

Krishnan, M., Rajagopal, V., and Rathinasamy, S., “Performance evaluation of sensor deployment using optimization techniques and scheduling approach for k-coverage in WSNsâ€, Wireless Networks, vol. 24, no. 3, pp. 683-693, 2018. DOI: https://doi.org/10.1007/s11276-016-1361-5

Kumari, S., and Gupta, G. P., “Cuckoo search optimization based mobile node deployment scheme for target coverage problem in underwater wireless system networksâ€, International Conference on Intelligent Data Communication Technologies and Internet of Things, pp. 327-334, 2018. DOI: https://doi.org/10.1007/978-3-030-03146-6_36

Matula D. W., Marble, G., and Isaacson, J. D., “Graph Coloring algorithmsâ€, Graph theory and computing, pp. 109-122, 1972. DOI: https://doi.org/10.1016/B978-1-4832-3187-7.50015-5

Mini, S., Udgata, S., and Sabat, S., “Sensor deployment and scheduling for target coverage problem in wireless sensor networks,†IEEE Sensors, Vol. 14, No. 3, pp. 636-644, 2014. DOI: https://doi.org/10.1109/JSEN.2013.2286332

Njoya, A. N., Abdou, W., Dipanda, A., and Tonye, E., “Evolutionary based wireless sensor deployment for target coverage,†Eleventh IEEE International Conference on Signal-Image Technology & Internet-Based Systems, pp. 739-745, 2015. DOI: https://doi.org/10.1109/SITIS.2015.62

Singh, D., Chand, S., and Kumar, B., “Genetic algorithm-based heuristic for solving target coverage problem in wireless sensor networksâ€, Advanced computing and communication technologies, pp. 257-264, 2018. DOI: https://doi.org/10.1007/978-981-10-4603-2_24

Sun, S., Sun, L., and Chen, S., “Research on the target coverage algorithms for 3D curved surface,†Chaos Solitons Fractals, vol. 89, pp. 397-404, 2016. DOI: https://doi.org/10.1016/j.chaos.2016.02.003

Temel, S., Unaldi, N., and Kaynak, O., “On deployment of wireless sensors on 3-D terrains to maximize sensing coverage by utilizing cat swarm optimization with wavelet transform,†IEEE Transactions on Systems, Man, Cybernetics: System., vol. 44, no. 1, pp. 111-120, 2014. DOI: https://doi.org/10.1109/TSMCC.2013.2258336

Unaldi, N., Temel, S., and Asari, V. K., “Method for optimal sensor deployment on 3D terrain utilizing a steady state genetic algorithm with a guided walk mutation operator based on the wavelet transform,†Sensors, vol. 12, no. 4, pp. 5116-5133, 2012. DOI: https://doi.org/10.3390/s120405116

Vijayaraju, P., Sripathy, B., Arivudainambi, D., and Balaji, S., “Hybrid memetic algorithm with two-dimensional discrete Haar wavelet transform for optimal sensor placement,†IEEE Sensors, vol. 17, no. 7, pp. 2267-2278, 2017. DOI: https://doi.org/10.1109/JSEN.2017.2662951

Wang, J., Ju, C., Gao, Y, Sangaiah, A. K., and Kim G. J., “A PSO based energy efficient coverage control algorithm for wireless sensor networksâ€, Computer Mater., Vol. 56, pp. 433-446, 2018.

Willig, A., “ Recent and emerging topics in wireless industrial communications: A selection,†IEEE Transactions on industrial informatics, vol. 4, no. 2, pp. 102-124, 2008. DOI: https://doi.org/10.1109/TII.2008.923194

Wu, T., Yang, P., Dai, H., Xu, W., and Xu, M., “Charging oriented sensor placement and flexible scheduling in rechargeable WSNsâ€, IEEE INFOCOM, pp. 73-81, 2019. DOI: https://doi.org/10.1109/INFOCOM.2019.8737502

Zhu, X., Li, J., and Zhou, M., “Optimal deployment of energy harvesting directional sensor networks for target coverageâ€, IEEE System Journal, vol. 13, no. 1, pp. 377-88, 2018. DOI: https://doi.org/10.1109/JSYST.2018.2820085

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Published

2021-01-03

How to Cite

[1]
P. Ravikumar and D. Arivudainambi, “Towards Efficient Sensor Placement for Industrial Wireless Sensor Network”, J. Ilm. Tek. Elektro Komput. Dan Inform, vol. 6, no. 2, pp. 58–69, Jan. 2021.

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Vol. 6 No. 2 (2020): December

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