Utilizing Genetic Algorithm and Artificial Bee Colony Algorithm to Extend the WSN Lifetime
Keywords:Wireless sensor network (WSN), Genetic algorithm (GA), Artificial Bee Colony (ABC), K-Means Clustering, Clustering based on GA, LEACH protocol
Extending the lifetime of Wireless Sensor Networks (WSN) is an important issue due to the mission assigned to these networks. The sensors collect data relevant to a specific field. Then, the sensors send the collected data to a base station where it is analyzed, and a suitable reaction can be taken. Sensors in WSN depend on a battery with limited energy to do their work. Data transmission and receiving consume energy, which may lead to the loss of the whole network or some of the essential nodes. For this reason, energy must be preserved as long as possible to prolong the network lifetime. Several types of research were presented with different approaches to minimize power consumption. In this paper, we present a hybrid technique that includes two population-based algorithms: genetic algorithm (GA) and artificial bee colony (ABC) with clustering approaches. This proposed novel technique aims to reduce the dissipation of power consumption per sensor node in the WSN, and as a consequence, the lifetime of the WSN is extended. The ABC algorithm was used to improve an initial population, which was used in the GA. Also, we used two approaches of clustering; clustering based on genetic algorithm and K-means clustering beside LEACH protocol. The experimental results show that the proposed approach approved its efficiency in lifetime extending through an increasing number of the operational nodes per round and transmission.
R. Srivastava and M. Hasan, “Comparative study on integration of wireless sensor network with cloud computing,” Int. J. Adv. Res. Comput. Sci., vol. 9, no. Special Issue 2, p. 185, 2018.
M. Carlos-Mancilla, E. López-Mellado, and M. Siller, “Wireless sensor networks formation: approaches and techniques,” J. Sensors, vol. 2016, Article ID 2081902, 2016. https://doi.org/10.1155/2016/2081902.
S. Panda, S. Srivastava, S. Mohapatra, and P. Kumar, “Performance analysis of wireless sensor networks using artificial bee colony algorithm,” Proceedings of the 2018 Technologies for Smart-City Energy Security and Power (ICSESP), 2018, pp. 1–5. https://doi.org/10.1109/ICSESP.2018.8376711.
A. Norouzi, F. S. Babamir, A. H. Zaim, and others, “A new clustering protocol for wireless sensor networks using genetic algorithm approach,” Wirel. Sens. Netw., vol. 3, no. 11, p. 362, 2011. https://doi.org/10.4236/wsn.2011.311042.
A. Norouzi and A. H. Zaim, “Genetic algorithm application in optimization of wireless sensor networks,” Sci. World J., vol. 2014, Article ID 286575, 2014. https://doi.org/10.1155/2014/286575.
P. Sasikumar and S. Khara, “K-means clustering in wireless sensor networks,” Proceedings of the 2012 Fourth international conference on computational intelligence and communication networks, 2012, pp. 140–144. https://doi.org/10.1109/CICN.2012.136.
W. Abushiba, P. Johnson, S. Alharthi, and C. Wright, “An energy efficient and adaptive clustering for wireless sensor network (CH-leach) using leach protocol,” Proceedings of the 2017 13th International Computer Engineering Conference (ICENCO), 2017, pp. 50–54. https://doi.org/10.1109/ICENCO.2017.8289762.
A. Gambhir, A. Payal, and R. Arya, “Performance analysis of artificial bee colony optimization based clustering protocol in various scenarios of WSN,” Procedia Comput. Sci., vol. 132, pp. 183–188, 2018. https://doi.org/10.1016/j.procs.2018.05.184.
B. Barekatain, S. Dehghani, and M. Pourzaferani, “An energy-aware routing protocol for wireless sensor networks based on new combination of genetic algorithm & k-means,” Procedia Comput. Sci., vol. 72, pp. 552–560, 2015. https://doi.org/10.1016/j.procs.2015.12.163.
P. Nayak and B. Vathasavai, “Genetic algorithm based clustering approach for wireless sensor network to optimize routing techniques,” Proceedings of the 2017 7th International Conference on Cloud Computing, Data Science & Engineering-Confluence, 2017, pp. 373–380. https://doi.org/10.1109/CONFLUENCE.2017.7943178.
A. O. A. Salem and N. Shudifat, “Enhanced LEACH protocol for increasing a lifetime of WSNs,” Pers. Ubiquitous Comput., vol. 23, no. 5–6, pp. 901–907, 2019. https://doi.org/10.1007/s00779-019-01205-4.
M. F. K. Abad and M. A. J. Jamali, “Modify LEACH algorithm for wireless sensor network,” Int. J. Comput. Sci. Issues, vol. 8, no. 5, p. 219, 2011.
A. Salim, W. Osamy, and A. M. Khedr, “IBLEACH: intra-balanced LEACH protocol for wireless sensor networks,” Wirel. networks, vol. 20, no. 6, pp. 1515–1525, 2014. https://doi.org/10.1007/s11276-014-0691-4.
B. A. Bakr and L. Lilien, “LEACH-SM: A protocol for extending wireless sensor network lifetime by management of spare nodes,” Proceedings of the 2011 International Symposium of Modeling and Optimization of Mobile, Ad Hoc, and Wireless Networks, 2011, p. 375. https://doi.org/10.1109/WIOPT.2011.5930046.
S. E. L. Khediri, N. Nasri, A. Wei, and A. Kachouri, “A new approach for clustering in wireless sensors networks based on LEACH,” Procedia Comput. Sci., vol. 32, pp. 1180–1185, 2014. https://doi.org/10.1016/j.procs.2014.05.551.
E. Heidari, A. Movaghar, and M. Mahramian, “The Usage of Genetic Algorithm in Clustering and Routing in Wireless Sensor Networks,” Advances in Intelligent Web Mastering-2, Springer, 2010, pp. 95–103. https://doi.org/10.1007/978-3-642-10687-3_9.
F. Tossa, W. Abdou, E. C. Ezin, and P. Gouton, “Improving Coverage Area in Sensor Deployment Using Genetic Algorithm,” Proceedings of the International Conference on Computational Science, 2020, pp. 398–408. https://doi.org/10.1007/978-3-030-50426-7_30.
M. Romoozi and H. Ebrahimpour-Komleh, “A positioning method in wireless sensor networks using genetic algorithms,” Phys. Procedia, vol. 33, pp. 1042–1049, 2012. https://doi.org/10.1016/j.phpro.2012.05.171.
H. Alazzam and W. Almobaideen, “Enhancing the lifetime of wireless sensor network using genetic algorithm,” Proceedings of the 2019 10th International Conference on Information and Communication Systems (ICICS), 2019, pp. 25–29. https://doi.org/10.1109/IACS.2019.8809109.
M. Abo-Zahhad, S. M. Ahmed, N. Sabor, and S. Sasaki, “A new energy-efficient adaptive clustering protocol based on genetic algorithm for improving the lifetime and the stable period of wireless sensor networks,” Int. J. Energy, Inf. Commun., vol. 5, no. 3, pp. 47–72, 2014. https://doi.org/10.14257/ijeic.2014.5.3.05.
M. K. Singh and P. Nagarathna, “Improvement in life span of wsn using genetic algorithm with new fitness function,” Proceedings of the IEEE International Conference on Electronics Computer Technology, 2012, pp. 1–23.
A. Mohajerani and D. Gharavian, “An ant colony optimization based routing algorithm for extending network lifetime in wireless sensor networks,” Wirel. Networks, vol. 22, no. 8, pp. 2637–2647, 2016. https://doi.org/10.1007/s11276-015-1061-6.
W. Zheng and D. Luo, “Routing in wireless sensor network using Artificial Bee Colony algorithm,” Proceedings of the 2014 International Conference on Wireless Communication and Sensor Network, 2014, pp. 280–284. https://doi.org/10.1109/WCSN.2014.64.
G. Y. Park, H. Kim, H. W. Jeong, and H. Y. Youn, “A novel cluster head selection method based on K-means algorithm for energy efficient wireless sensor network,” Proceedings of the 2013 27th International Conference on Advanced Information Networking and Applications Workshops, 2013, pp. 910–915.
D. Karaboga, S. Okdem, and C. Ozturk, “Cluster based wireless sensor network routing using artificial bee colony algorithm,” Wirel. Networks, vol. 18, no. 7, pp. 847–860, 2012. https://doi.org/10.1007/s11276-012-0438-z.
How to Cite
LicenseInternational Journal of Computing is an open access journal. Authors who publish with this journal agree to the following terms:
• Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
• Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
• Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.