Abstract
Wireless Sensor Networks (WSN) is an increasingly growing field, due to its enormous applications. In WSNs, energy conservation is the most important design challenge. In WSNs, unequal clustering can be classified as the best data transmission method that saves energy, where the size of the cluster changes in proportion to the cluster head’s (CH’s) distance from the base station (BS), so as to prevent energy holes/hot-spots from being formed. We have developed GA-UCR in this paper, a “Genetic Algorithm based Unequal Clustering and Routing Protocol for Wireless Sensor Networks”. For CH election, genetic algorithm (GA) has been utilized with three fitness functions- remaining energy of CH nodes, distance between CH and BS/sink, and inter-cluster separation. For inter-cluster multi-hopping, to route the data towards BS, again GA is utilized due to the NP-Hard nature of the problem, with three fitness functions-residual/remaining energy of next hop nodes, CH to next hop node distance and number of hops. Simulation outcomes and analysis show that with reference to energy consumption, network lifetime and scalability, the proposed algorithm exceeds the existing algorithms such as Direct propagation, LEACH, TL-LEACH, GCA, EAERP and GAECH.
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Arampatzis, T., Lygeros, J., & Manesis, S. (2005). A survey of applications of wireless sensors and wireless sensor networks. In Intelligent control, 2005. Proceedings of the 2005 IEEE international symposium on, mediterrean conference on control and automation. IEEE.
Al-Karaki, J. N., & Kamal, A. E. (2004). Routing techniques in wireless sensor networks: A survey. IEEE Wireless Communications, 11(6), 6–28.
Puccinelli, D., & Haenggi, M. (2005). Wireless sensor networks: Applications and challenges of ubiquitous sensing. IEEE Circuits and Systems Magazine, 5(3), 19–31.
Yick, J., Mukherjee, B., & Ghosal, D. (2008). Wireless sensor network survey. Computer Networks, 52(12), 2292–2330.
Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 1(4), 660–670.
Younis, M., & Akkaya, K. (2008). Strategies and techniques for node placement in wireless sensor networks: A survey. Ad Hoc Networks, 6(4), 621–655.
Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In System sciences, 2000. Proceedings of the 33rd annual Hawaii international conference on. IEEE.
Intanagonwiwat, C., Govindan, R., & Estrin, D. (2000). Directed diffusion: A scalable and robust communication paradigm for sensor networks. In Proceedings of the 6th annual international conference on Mobile computing and networking. ACM.
Heinzelman, W. R., Kulik, J., & Balakrishnan, H. Adaptive protocols for information dissemination in wireless sensor networks. In Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking. ACM.
Lindsey, S., & Raghavendra, C. S. (2002). PEGASIS: Power-efficient gathering in sensor information systems. In Proceedings, IEEE aerospace conference (Vol. 3). IEEE.
Kang, S. H., & Nguyen, T. (2012). Distance based thresholds for cluster head selection in wireless sensor networks. IEEE Communications Letters, 16(9), 1396–1399.
Manjeshwar, A., & Agrawal, D. P. (2001). TEEN: A routing protocol for enhanced efficiency in wireless sensor networks. In Null. IEEE.
Khalil, E. A., & Bara’a, A. A. (2011). Energy-aware evolutionary routing protocol for dynamic clustering of wireless sensor networks. Swarm and Evolutionary Computation, 1(4), 195–203.
Tripathi, R. K., Singh, Y. N., & Verma, N. K. (2012). N-leach, a balanced cost cluster-heads selection algorithm for wireless sensor network. In Communications (NCC), 2012 national conference on. IEEE.
Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 1(4), 660–670.
Loscri, V., Morabito, G., & Marano, S. (2005). A two-levels hierarchy for low-energy adaptive clustering hierarchy (TL-LEACH). In Vehicular technology conference, 2005. VTC-2005-Fall. 2005 IEEE 62nd (Vol. 3). IEEE.
Neto, J. H. B., Rego, A., Cardoso, A. R., & Celestino, J. (2014). MH-LEACH: A distributed algorithm for multi-hop communication in wireless sensor networks. ICN, 2014, 55–61.
Perillo, M., Cheng, Z., & Heinzelman, W. (2005). Strategies for mitigating the sensor network hot spot problem. In Proceedings of MobiQuitous.
Perillo, M., Cheng, Z., Heinzelman, W. (2004). On the problem of unbalanced load distribution in wireless sensor networks. In IEEE Global Telecommunications Conference Workshops, 2004. GlobeCom Workshops 2004. IEEE.
Jaichandran, R., & Irudhayaraj, A. A. (2010). Effective strategies and optimal solutions for hot spot problem in wireless sensor networks (WSN). In 10th international conference on information science, signal processing and their applications (ISSPA 2010). IEEE.
Younis, O., & Fahmy, S. (2004). HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing, 3(4), 366–379.
Yu, J., Qi, Y., Wang, G., Guo, Q., & Gu, X. (2011). An energy-aware distributed unequal clustering protocol for wireless sensor networks. International Journal of Distributed Sensor Networks, 7(1), 202145.
Gupta, V., & Pandey, R. (2016). An improved energy aware distributed unequal clustering protocol for heterogeneous wireless sensor networks. Engineering Science and Technology, an International Journal, 19(2), 1050–1058.
Bagci, H., & Yazici, A. (2013). An energy aware fuzzy approach to unequal clustering in wireless sensor networks. Applied Soft Computing, 13(4), 1741–1749.
Jiang, C.-J., Shi, W.-R., & Tang, X.-L. (2010). Energy-balanced unequal clustering protocol for wireless sensor networks. The Journal of China Universities of Posts and Telecommunications, 17(4), 94–99.
Abo-Zahhad, M., Ahmed, S. M., Sabor, N., & Sasaki, S. (2014). A new energy-efficient adaptive clustering protocol based on genetic algorithm for improving the lifetime and the stable period of wireless sensor networks. International Journal of Energy, Information and Communications, 5(3), 47–72.
Soro, S., & Heinzelman, W. B. (2005). Prolonging the lifetime of wireless sensor networks via unequal clustering. In 19th IEEE international parallel and distributed processing symposium. IEEE.
Ye, M., Li, C., Chen, G., & Wu, J. (2005). EECS: An energy efficient clustering scheme in wireless sensor networks. In PCCC 2005. 24th IEEE international performance, computing, and communications conference, 2005. IEEE.
Li, C., Ye, M., Chen, G., & Wu, J. (2005). An energy-efficient unequal clustering mechanism for wireless sensor networks. In IEEE international conference on mobile adhoc and sensor systems conference. IEEE.
Gong, B., Li, L., Wang, S., & Zhou, X. (2008). Multihop routing protocol with unequal clustering for wireless sensor networks. In 2008 ISECS international colloquium on computing, communication, control, and management (Vol. 2). IEEE.
Baniata, M., & Hong, J. (2017). Energy-efficient unequal chain length clustering for wireless sensor networks in smart cities. Wireless Communications and Mobile Computing, 2017.
Baranidharan, B., & Santhi, B. (2015). GAECH: genetic algorithm based energy efficient clustering hierarchy in wireless sensor networks. Journal of Sensors, 2015.
Gen, M., & Lin, L. (2007). Genetic algorithms. Wiley Encyclopedia of Computer Science and Engineering, 1-15.
Gunjan. (2022). A Review on Multi-objective Optimization in Wireless Sensor Networks Using Nature Inspired Meta-heuristic Algorithms. NEURAL PROCESSING LETTERS.
Liu, J.-L., & Ravishankar, C. V. (2011). LEACH-GA: Genetic algorithm-based energy-efficient adaptive clustering protocol for wireless sensor networks. International Journal of Machine Learning and Computing, 1(1), 79.
Gupta, S. K., & Jana, P. K. (2015). Energy efficient clustering and routing algorithms for wireless sensor networks: GA based approach. Wireless Personal Communications, 83(3), 2403–2423.
Wang, T., Zhang, G., Yang, X., & Vajdi, A. (2018). Genetic algorithm for energy-efficient clustering and routing in wireless sensor networks. Journal of Systems and Software, 146, 196–214.
Mudundi, S., & Ali, H. H. (2007). A new robust genetic algorithm for dynamic cluster formation in wireless sensor networks. In Proceedings of Wireless and Optical Communications, Montreal.
Farooq, M. O., Dogar, A. B., & Shah, G. A. (2010). MR-LEACH: Multi-hop routing with low energy adaptive clustering hierarchy. In 2010 4th international conference on sensor technologies and applications. IEEE.
Liu, J.-L., & Ravishankar, C. V. (2011). LEACH-GA: Genetic algorithm-based energy-efficient adaptive clustering protocol for wireless sensor networks. International Journal of Machine Learning and Computing, 1(1), 79.
Bayraklı, S., & Erdogan, S. Z. (2012). Genetic algorithm based energy efficient clusters (GABEEC) in wireless sensor networks. Procedia Computer Science, 10, 247–254.
Gajjar, S., Sarkar, M., & Dasgupta, K. (2016). FAMACROW: Fuzzy and ant colony optimization based combined mac, routing, and unequal clustering cross-layer protocol for wireless sensor networks. Applied Soft Computing, 43, 235–247.
Whitley, D. (1994). A genetic algorithm tutorial. Statistics and Computing, 4(2), 65–85.
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Gunjan, Sharma, A.K. & Verma, K. GA-UCR: Genetic Algorithm Based Unequal Clustering and Routing Protocol for Wireless Sensor Networks. Wireless Pers Commun 128, 537–558 (2023). https://doi.org/10.1007/s11277-022-09966-7
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DOI: https://doi.org/10.1007/s11277-022-09966-7