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Communication Papers of the 17th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 32

Ant Colony based Coverage Optimization in Wireless Sensor Networks

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DOI: http://dx.doi.org/10.15439/2022F177

Citation: Communication Papers of the 17th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 32, pages 155159 ()

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Abstract. Maximizing the covered area of wireless sensor networks while keeping the connectivity between the nodes is one of the challenging tasks in wireless sensor networks deployments. In this paper we propose an ant colony-based method for the problem of sensor nodes deployment to maximize the coverage area. We model sensor locations as a graph and use an adapted ant colony optimization-based method to find the best places for each sensor node. To keep the connectivity of the sensor network, every sensor must be covered by the other sensors; this is a hard constraint that is applied to the cost function as a penalty. The proposed algorithm is evaluated with different number of sensor nodes and sensing ranges. The simulation results showed that increasing the number of iterations in the algorithm generates better coverage ratio with the same number of nodes.


  1. Sadik Arslan, Moharram Challenger, Orhan Dagdeviren, "Wireless sensor network based fire detection system for libraries", International Conference on Computer Science and Engineering (UBMK), IEEE, Antalya, Turkey, 05-08 October 2017.
  2. Harizan, Subash, and Pratyay Kuila. "Evolutionary algorithms for coverage and connectivity problems in wireless sensor networks: a study." Design frameworks for wireless networks. Springer, Singapore, 2020. 257-280.
  3. Al-Fuhaidi, Belal, et al. "An efficient deployment model for maximizing coverage of heterogeneous wireless sensor network based on harmony search algorithm." Journal of Sensors 2020 (2020).
  4. Wang, Lei, et al. "Wireless sensor network coverage optimization based on whale group algorithm." Computer Science and Information Systems 15.3 (2018): 569-583.
  5. Wang, Hui, et al. "A self-deployment algorithm for maintaining maximum coverage and connectivity in underwater acoustic sensor networks based on an ant colony optimization." Applied Sciences 9.7 (2019): 1479.
  6. Farsi, Mohammed, et al. "Deployment techniques in wireless sensor networks, coverage and connectivity: A survey." Ieee Access 7 (2019): 28940-28954.
  7. Yoon, Yourim, and Yong-Hyuk Kim. "An efficient genetic algorithm for maximum coverage deployment in wireless sensor networks." IEEE Transactions on Cybernetics 43.5 (2013): 1473-1483.
  8. Kong, Hongshan, and Bin Yu. "An improved method of WSN coverage based on enhanced PSO algorithm." 2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC). IEEE, 2019.
  9. Tossa, Frantz, Wahabou Abdou, Eugène C. Ezin, and Pierre Gouton. "Improving coverage area in sensor deployment using genetic algorithm." International Conference on Computational Science. Springer, Cham, 2020.
  10. Zorlu, Ozan, and Ozgur Koray Sahingoz. "Increasing the coverage of homogeneous wireless sensor network by genetic algorithm based deployment." 2016 Sixth International Conference on Digital Information and Communication Technology and its Applications (DICTAP). IEEE, 2016.
  11. Zhu, Fang, and Wenhao Wang. "A coverage optimization method for WSNs based on the improved weed algorithm." Sensors 21.17 (2021): 5869.
  12. Liu, Xuxun, and Desi He. "Ant colony optimization with greedy migration mechanism for node deployment in wireless sensor networks." Journal of Network and Computer Applications 39 (2014): 310-318.
  13. Liao, Wen-Hwa, Yucheng Kao, and Ru-Ting Wu. "Ant colony optimization based sensor deployment protocol for wireless sensor networks." Expert Systems with Applications 38.6 (2011): 6599-6605.
  14. Qasim, Tehreem, et al. "ACO-Discreet: An efficient node deployment approach in wireless sensor networks." Information technology-new generations. Springer, Cham, (2018). 43-48.
  15. Sun, Zeyu, Weiguo Wu, Huanzhao Wang, Heng Chen, and Wei Wei. "An optimized strategy coverage control algorithm for WSN." International Journal of Distributed Sensor Networks 10.7 (2014): 976307.
  16. Li, Dong, Wei Liu, and Li Cui. "EasiDesign: an improved ant colony algorithm for sensor deployment in real sensor network system." 2010 IEEE Global Telecommunications Conference GLOBECOM 2010. IEEE, 2010.
  17. Fathima, K. Syed Ali, and K. Sindhanaiselvan. "Ant colony optimization based routing in wireless sensor networks." International Journal of Advanced Networking and Applications 4.4 (2013): 168