Increasing Coverage in Wireless Sensor Networks by Minimizing Displacements Using a Greedy Method based on Nodes’ Location and Neighborhood

  • Yaser Mehregan
  • Keyvan Mohebbi Department of Electrical and Computer Engineering, Mobarakeh Branch, Islamic Azad University, Mobarakeh, Isfahan, Iran. - Department of Computer Engineering, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.
Keywords: Energy consumption, Wireless sensor network, Coverage, Nodes’ displacement, Nodes’ neighborhood


The successful operation of a wireless sensor network depends on the proper coverage of the environment, which in turn is affected by the number and location of sensors. In most cases, the sensors are placed randomly in the deployment region, so by default, most coverage is not achieved in their initial deployment. One of the major challenges for network design is to determine the location strategy of the sensors so that the deployed nodes can cover as many regions as possible. The objective of this study is to solve this problem in such a way that the energy consumption of the nodes is minimal. Because the power supply of the sensor nodes is a non-rechargeable battery. The proposed approach uses division and detection of uncovered regions. Then a greedy method based on the topology and properties of the nodes and the network deployment region is presented to select the optimal nodes and cover the region. The proposed approach is simulated and the evaluation results show a decrease in the displacement of the sensors for more coverage and a reduction in energy consumption compared to similar works.


[1] S. Biswas, R. Das, and P. Chatterjee, "Energy-efficient connected target coverage in multi-hop wireless sensor networks," in Industry interactive innovations in science, engineering and technology: Springer, 2018, pp. 411-421.
[2] W. Fang, X. Song, X. Wu, J. Sun, and M. Hu, "Novel efficient deployment schemes for sensor coverage in mobile wireless sensor networks," Information Fusion, vol. 41, pp. 25-36, 2018.
[3] H. Yetgin, K. T. K. Cheung, M. El-Hajjar, and L. H. Hanzo, "A survey of network lifetime maximization techniques in wireless sensor networks," IEEE Communications Surveys & Tutorials, vol. 19, no. 2, pp. 828-854, 2017.
[4] M. Pule, A. Yahya, and J. Chuma, "Wireless sensor networks: A survey on monitoring water quality," Journal of applied research and technology, vol. 15, no. 6, pp. 562-570, 2017.
[5] E. Fadel et al., "A survey on wireless sensor networks for smart grid," Computer Communications, vol. 71, pp. 22-33, 2015.
[6] K. Mehta and R. Pal, "Energy efficient routing protocols for wireless sensor networks: A survey," International Journal of Computer Applications, vol. 165, no. 3, pp. 41-46, 2017.
[7] Y. Li and S. Gao, "Designing k-coverage schedules in wireless sensor networks," Journal of Combinatorial Optimization, vol. 15, no. 2, pp. 127-146, 2008.
[8] Z. Yuan, L. Wang, L. Shu, T. Hara, and Z. Qin, "A balanced energy consumption sleep scheduling algorithm in wireless sensor networks," in 2011 7th International Wireless Communications and Mobile Computing Conference, 2011, pp. 831-835: IEEE.
[9] S. K. Udgata, S. L. Sabat, and S. Mini, "Sensor deployment in irregular terrain using artificial bee colony algorithm," in 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 2009, pp. 1309-1314: IEEE.
[10] F. M. Al-Turjman, H. S. Hassanein, and M. A. Ibnkahla, "Efficient deployment of wireless sensor networks targeting environment monitoring applications," Computer Communications, vol. 36, no. 2, pp. 135-148, 2013.
[11] H. Mahboubi, K. Moezzi, A. G. Aghdam, K. Sayrafian-Pour, and V. Marbukh, "Distributed deployment algorithms for improved coverage in a network of wireless mobile sensors," IEEE Transactions on Industrial Informatics, vol. 10, no. 1, pp. 163-174, 2013.
[12] M. Mansour and F. Jarray, "An iterative solution for the coverage and connectivity problem in wireless sensor network," Procedia Computer Science, vol. 63, pp. 494-498, 2015.
[13] A. Ray and D. De, "An energy efficient sensor movement approach using multi-parameter reverse glowworm swarm optimization algorithm in mobile wireless sensor network," Simulation modelling practice and theory, vol. 62, pp. 117-136, 2016.
[14] J. Roselin, P. Latha, and S. Benitta, "Maximizing the wireless sensor networks lifetime through energy efficient connected coverage," Ad Hoc Networks, vol. 62, pp. 1-10, 2017.
[15] G. Sun, Y. Liu, H. Li, A. Wang, S. Liang, and Y. Zhang, "A novel connectivity and coverage algorithm based on shortest path for wireless sensor networks," Computers & Electrical Engineering, vol. 71, pp. 1025-1039, 2018.
[16] N. T. Hanh, H. T. T. Binh, N. X. Hoai, and M. S. Palaniswami, "An efficient genetic algorithm for maximizing area coverage in wireless sensor networks," Information Sciences, vol. 488, pp. 58-75, 2019.
[17] D.-R. Chen, L.-C. Chen, M.-Y. Chen, and M.-Y. Hsu, "A coverage-aware and energy-efficient protocol for the distributed wireless sensor networks," Computer Communications, vol. 137, pp. 15-31, 2019.
[18] H. Wu, Q. Li, H. Zhu, X. Han, Y. Li, and B. Yang, "Directional sensor placement in vegetable greenhouse for maximizing target coverage without occlusion," Wireless Networks, vol. 26, pp. 4677-4687, 2020.
[19] V. A. Sateesh, A. Kumar, R. Priyadarshi, and V. Nath, "A Novel Deployment Scheme to Enhance the Coverage in Wireless Sensor Network," in Proceedings of the Fourth International Conference on Microelectronics, Computing and Communication Systems, 2021, pp. 985-993: Springer.
[20] S.-C. Wang, H. C. Hsiao, C.-C. Lin, and H.-H. Chin, "Multi-Objective Wireless Sensor Network Deployment Problem with Cooperative Distance-Based Sensing Coverage," Mobile Networks and Applications, pp. 1-12, 2021.
[21] X. Xu, J. Tang, and H. Xiang, "Data Transmission Reliability Analysis of Wireless Sensor Networks for Social Network Optimization," Journal of Sensors, vol. 2022, 2022.
[22] X. Wu, Z. Chen, Y. Zhong, H. Zhu, and P. Zhang, "End-to-end data collection strategy using mobile sink in wireless sensor networks," International Journal of Distributed Sensor Networks, vol. 18, no. 3, p. 15501329221077932, 2022.
[23] W. B. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan, "An application-specific protocol architecture for wireless microsensor networks," IEEE Transactions on wireless communications, vol. 1, no. 4, pp. 660-670, 2002.
[24] A. W. Khan, A. H. Abdullah, M. A. Razzaque, and J. I. Bangash, "VGDRA: a virtual grid-based dynamic routes adjustment scheme for mobile sink-based wireless sensor networks," IEEE sensors journal, vol. 15, no. 1, pp. 526-534, 2014.
How to Cite
Mehregan, Y., & Mohebbi, K. (2022). Increasing Coverage in Wireless Sensor Networks by Minimizing Displacements Using a Greedy Method based on Nodes’ Location and Neighborhood. Majlesi Journal of Electrical Engineering, 16(2). Retrieved from