Abstract
Recently, many researchers have paid attention to wireless sensor networks (WSNs) due to their ability to encourage the innovation of the IT industry. Although WSN provides dynamically scalable solutions with various smart applications, the growing need to maximize the area coverage with decreasing the percentage of deployed sensor nodes is still required. Random deployment is preferable for large areas that require a maximal number of nodes but result in coverage holes. As a result, mobile nodes are used to reduce coverage holes and maximize area coverage. The main objective of this study is to present an Improved Dynamic Deployment Technique based-on Genetic Algorithm (IDDT-GA) to maximize the area coverage with the lowest number of nodes as well as minimizing overlapping area between neighboring nodes. A two-point crossover novel is introduced to demonstrate the notation of variable-length encoding. Simulation results reveal that the superiority of the proposed IDDT-GA compared with other state-of-the-art techniques. IDDT-GA has better coverage rates with 9.69% and a minimum overlapping ratio with 35.43% compared to deployment based on Harmony Search (HS). Also, IDDT-GA has minimized the network cost by 13% and 7.44% than Immune Algorithm (IA) and Whale Optimization Algorithm (WOA) respectively. Besides, it confirms its stability with 83.04% compared to maximizing coverage with WOA.
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References
Abo-Zahhad M, Ahmed SM, Sabor N, Sasaki S (2014) Coverage maximization in mobile wireless sensor networks utilizing immune node deployment algorithm. In: Electrical and Computer Engineering (CCECE), 2014 IEEE 27th Canadian Conference on IEEE, pp 1–6. https://doi.org/10.1109/CCECE.2014.6901069
Ali A, Ming Y, Chakraborty S, Iram S (2017) A comprehensive survey on real-time applications of wsn. Future Internet 9(4):77. https://doi.org/10.3390/fi9040077
Aponte-Luis J, Gómez-Galán JA, Gómez-Bravo F, Sánchez-Raya M, Alcina-Espigado J, Teixido-Rovira PM (2018) An efficient wireless sensor network for industrial monitoring and control. Sensors 18(1):182. https://doi.org/10.3390/s18010182
Bala T, Bhatia V, Kumawat S, Jaglan V (2018) A survey: issues and challenges in wireless sensor network. Int J Eng Technol 7(24). https://doi.org/10.14419/ijet.v7i2.4.10041
Banoori F, Kashif M, Arslan M, Chakma R, Khan F, Al Mamun A (2018) Deployment techniques of nodes in wsn and survey on their performance analysis. In: 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018). Atlantis Press. http://dx.doi.org/10.2991/acaai-18.2018.55
Binh HTT, Hanh NT, Dey N et al (2018) Improved cuckoo search and chaotic flower pollination optimization algorithm for maximizing area coverage in wireless sensor networks. Neural Comput Appl 30(7):2305–2317. https://doi.org/10.1007/s00521-016-2823-5
Boualem A, Dahmani Y, Maatoug A, De Runz C (2018) Area coverage optimization in wireless sensor network by semi-random deployment. In: SENSORNETS, pp 85–90. https://doi.org/10.5220/0006581900850090
Chien TV, Chan HN, Huu TN (2012) A comparative study on hardware platforms for wireless sensor networks. Int J Adv Sci Eng Inf Technol 2(1):70–74. https://doi.org/10.18517/ijaseit.2.1.157
Du K-L, Swamy M (2016) Simulated annealing. In: Search and Optimization by Metaheuristics, Springer, pp 29–36. https://doi.org/10.1007/978-3-319-41192-7_2
El Khamlichi Y, Tahiri A, Abtoy A, Medina-Bulo I, Palomo-Lozano F (2017) A hybrid algorithm for optimal wireless sensor network deployment with the minimum number of sensor nodes. Algorithms 10(3):80. https://doi.org/10.3390/a10030080
Elma KJ, Meenakshi S (2019) Optimal coverage along with connectivity maintenance in heterogeneous wireless sensor network. In: Journal of Ambient Intelligence and Humanized Computing, pp 1–12. https://doi.org/10.1007/s12652-019-01621-7
Ezhilarasi M, Krishnaveni V (2018) A survey on wireless sensor network: energy and lifetime perspective. In: Taga Journal of Graphic Technology, 14. https://doi.org/10.13140/RG.2.2.11629.69606
Farsi M, Elhosseini MA, Badawy M, Arafat H, ZainEldin H (2019) Deployment techniques in wireless sensor networks, coverage and connectivity: a survey. IEEE Access. https://doi.org/10.1109/ACCESS.2019.2902072
Gupta SK, Kuila P, Jana PK (2016) Genetic algorithm approach for k-coverage and m-connected node placement in target based wireless sensor networks. Comput Electr Eng 56:544–556. https://doi.org/10.1016/j.compeleceng.2015.11.009
Hanh NT, Binh HTT, Hoai NX, Palaniswami MS (2019) An efficient genetic algorithm for maximizing area coverage in wireless sensor networks. Inf Sci 488:58–75. https://doi.org/10.1016/j.ins.2019.02.059
Jha SK, Eyong EM (2018) An energy optimization in wireless sensor networks by using genetic algorithm. Telecommun Syst 67(1):113–121. https://doi.org/10.1007/s11235-017-0324-1
Kalayci TE, Yildirim KS, Ugur A (2007) Maximizing coverage in a connected and k-covered wireless sensor network using genetic algorithms. Int J Appl Math Inf 1(3):123–130. https://doi.org/10.13140/2.1.4541.9527
Khoufi I, Minet P, Laouiti A, Mahfoudh S (2016) Survey of deployment algorithms in wireless sensor networks: coverage and connectivity issues and challenges. Int J Auton Adapt Commun Syst (IJAACS) 10(4):341–390. https://doi.org/10.1504/IJAACS.2017.088774
Kramer O (2017) Genetic algorithms. In: Genetic algorithm essentials, pp 11–19. Springer. https://doi.org/10.1007/978-3-319-52156-5_2
Mahamuni CV (2016) A military surveillance system based on wireless sensor networks with extended coverage life. In: 2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC), pp 375–381. https://doi.org/10.1109/ICGTSPICC.2016.7955331
Mnasri S, Thaljaoui A, Nasri N, Val T (2015) A genetic algorithm-based approach to optimize the coverage and the localization in the wireless audio-sensors networks. In: Networks, Computers and Communications (ISNCC), 2015 International Symposium on IEEE, pp 1–6. https://doi.org/10.1109/ISNCC.2015.7238591
Moh’d Alia O, Al-Ajouri A (2017) Maximizing wireless sensor network coverage with minimum cost using harmony search algorithm. IEEE Sens J 17(3):882–896. https://doi.org/10.1109/JSEN.2016.2633409
More A, Raisinghani V (2017) A survey on energy efficient coverage protocols in wireless sensor networks. J King Saud Univ Comput Inf Sci 29(4):428–448. https://doi.org/10.1016/j.jksuci.2016.08.001
Mostafaei H, Montieri A, Persico V, Pescapé A (2016) An efficient partial coverage algorithm for wireless sensor networks. In: 2016 IEEE Symposium on Computers and Communication (ISCC), pp 501–506. https://doi.org/10.1109/ISCC.2016.7543788
Mostafaei H, Obaidat MS (2017) A greedy overlap-based algorithm for partial coverage of heterogeneous wsns. In: GLOBECOM 2017-2017 IEEE Global Communications Conference, pp 1–6. https://doi.org/10.1109/GLOCOM.2017.8254431
Musa A, Gonzalez V, Barragan D (2019) A new strategy to optimize the sensors placement in wireless sensor networks. J Ambient Intell Humaniz Comput 10(4):1389–1399. https://doi.org/10.1007/s12652-018-0868-2
Nehra V, Sharma AK, Tripathi RK (2019) I-deec: improved deec for blanket coverage in heterogeneous wireless sensor networks. J Ambient Intell Hum Comput. https://doi.org/10.1007/s12652-019-01552-3
Özdağ R, CANAYAZ M (2017) A new dynamic deployment approach based on whale optimization algorithm in the optimization of coverage rates of wireless sensor networks. Eur J Technique 7(2):119–130. https://doi.org/10.23884/ejt.2017.7.2.06
Öztürk C, Karaboğa D, GÖRKEMLİ B (2012) Artificial bee colony algorithm for dynamic deployment of wireless sensor networks. Turkish J Electr Eng Comput Sci 20(2):255–262. https://doi.org/10.3906/elk-1101-1030
Priyadarshini RR, Sivakumar N (2019) Enhancing coverage and connectivity using energy prediction method in underwater acoustic wsn. J Ambient Intell Hum Comput. https://doi.org/10.1007/s12652-019-01334-x
Rebai M, Snoussi H, Hnaien F, Khoukhi L et al (2015) Sensor deployment optimization methods to achieve both coverage and connectivity in wireless sensor networks. Comput Oper Res 59:11–21. https://doi.org/10.1016/j.cor.2014.11.002
Sengupta S, Das S, Nasir M, Panigrahi BK (2013) Multi-objective node deployment in wsns: in search of an optimal trade-off among coverage, lifetime, energy consumption, and connectivity. Eng Appl Artif Intell 26(1):405–416. https://doi.org/10.1016/j.engappai.2012.05.018
Sharma V, Patel R, Bhadauria H, Prasad D (2016) Deployment schemes in wireless sensor network to achieve blanket coverage in large-scale open area: a review. Egypt Inf J 17(1):45–56. https://doi.org/10.1016/j.eij.2015.08.003
Singh A, Sharma T (2014) A survey on area coverage in wireless sensor networks. In: Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 2014 International Conference on IEEE, pp 829–836. https://doi.org/10.1109/ICCICCT.2014.6993073
Sivanandam S, Deepa S (2008) Genetic algorithms. In: Introduction to genetic algorithms, pp 15–37, Springer. https://doi.org/10.1007/978-3-540-73190-0_2
Su S, Zhao S (2017) A hierarchical hybrid of genetic algorithm and particle swarm optimization for distributed clustering in large-scale wireless sensor networks. J Ambient Intell Hum Comput. https://doi.org/10.1007/s12652-017-0619-9
Tian H (2019) Vigilnet:an integrated sensor network system for energy-efficient surveillance. https://www.cs.virginia.edu/wsn/vigilnet/. [Online; accessed 8-July-2019]
Tripathi A, Gupta HP, Dutta T, Mishra R, Shukla K, Jit S (2018) Coverage and connectivity in wsns: a survey, research issues and challenges. IEEE Access 6:26971–26992. https://doi.org/10.1109/ACCESS.2018.2833632
Tuba E, Tuba M, Beko M (2017) Mobile wireless sensor networks coverage maximization by firefly algorithm. In: Radioelektronika (RADIOELEKTRONIKA), 2017 27th International Conference, pp 1–5. https://doi.org/10.1109/RADIOELEK.2017.7937592
Wolpert DH, Macready WG et al (1997) No free lunch theorems for optimization. IEEE Trans Evol Comput 1(1):67–82. https://doi.org/10.1109/4235.585893
Zhu C, Zheng C, Shu L, Han G (2012) A survey on coverage and connectivity issues in wireless sensor networks. J Netw Comput Appl 35(2):619–632. https://doi.org/10.1016/j.jnca.2011.11.016
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ZainEldin, H., Badawy, M., Elhosseini, M. et al. An improved dynamic deployment technique based-on genetic algorithm (IDDT-GA) for maximizing coverage in wireless sensor networks. J Ambient Intell Human Comput 11, 4177–4194 (2020). https://doi.org/10.1007/s12652-020-01698-5
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DOI: https://doi.org/10.1007/s12652-020-01698-5