Abstract
In this work, a new protocol is proposed for sender-based responsive techniques on energy, mobility, and effective routing for Wireless Sensor Networks (WSNs). It addresses diverse challenges in packet routing especially, node mobility, energy optimization, and energy balancing in WSNs communication. The proposed protocol improves the basic Quality of Service (QoS) metrics such as Delay, Hop-Count, and Energy Level for each connection with multiple routes and predicts the best optimal path to develop efficient communication among them. It takes energy and performs mobility prediction and the time of connection failures. The main aim of this paper is to propose a secured and energy-efficient routing protocol using fuzzy rules and a node's trust values. Moreover, the proposed model provides an additional route and hence works without link failure. The observational result shows that the proposed protocol performs better than the existing secure routing protocols and achieves a packet delivery ratio of 20% higher than existing approaches. As per energy consumption, the proposed system obtains 15% lesser than recent approaches in secure energy-efficient routing protocols for WSNs.
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References
Adel, G. A., Elrahim, H. A., Elsayed, S. E., Ramly, M. M., & Ibrahim. (2010). An Energy-Aware+ WSN Geographic Routing Protocol. Universal Journal of Computer Science and Engineering Technology, 1(2), 105–111.
Liu, M., Cao, J., Chen, G., & Wang, X. (2009). An Energy-Aware Routing Protocol in Wireless Sensor Networks. Journal of Sensors, 9, 445–462.
Swapna Kumar, S., Nanda Kumar, M., Sheeba, V. S., & Kashwan, K. R. (2012). Cluster-Based Routing Algorithm Using Dual Staged Fuzzy Logic in Wireless Sensor Networks. Journal of Information Computational Science, 9(5), 1281–1297.
Yang, J., Zhao, W., Mai, Xu., & Baoguo, Xu. (2009). A Multipath Routing Protocol Based on Clustering and ACO for WSNs. International Journal of Computer Network and Information Security, 10, 4521–4540.
Selvakumar, K., Marimuthu Karuppiah, L., SaiRamesh, S. K., Islam, M. M., Hassan, G. F., & Choo, K. R. (2019). Intelligent temporal classification and fuzzy rough set-based feature selection algorithm for intrusion detection system in WSNs. Information Sciences, 497, 77–90.
Haider, T., & Yusuf, M. (2009). A fuzzy approach to energy-optimized routing for wireless sensor networks. The International Arab Journal of Information Technology, 6(2), 179–188.
Ran, Ge., Zhang, H., & Gong, S. (2010). Improving on LEACH protocol of wireless sensor networks using fuzzy logic. Journal of Information and Computational Science, 7(3), 767–775.
Begum, S., Tara, N., & Sultana, S. (2010). Energy-efficient target coverage in wireless sensor networks based on modified Ant Colony Algorithm. International Journal of Ad Hoc, Sensor & Ubiquitous Computing, 1(4), 29–36.
Nikravan, M., Jameii, S. M., & Kashani, M. H. (2011). An intelligent energy-efficient QoS-routing scheme for WSN. International Journal of Advanced Engineering Sciences and Technologies, 8(1), 121–124.
Akkaya, K., & Younis, M. (2004). Energy-aware, delay-constrained routing in WSNs through Genetic Algorithm. International Journal of Communication Systems, 17(6), 663–687.
Sethukkarasi, R. (2014). Sannasi Ganapathy, Yogesh Palanichamy, Arputharaj Kannan, “An intelligent neuro-fuzzy temporal knowledge representation model for mining temporal patterns.” Journal of Intelligent and Fuzzy Systems, 26(3), 1167–1178.
Faizal Khan, Z., & Kannan, A. (2014). Intelligent approach for segmenting CT lung images using fuzzy logic with bitplane. Journal of Electrical Engineering and Technology, 9, 742–752.
Sharma, A., Shinghal, K., Srivastava, N., & Singh, R. (2011). Energy management for wireless sensor network nodes. International Journal of Advances in Engineering & Technology, 1(1), 7–13.
Anastasi, G., Conti, M., Francesco, D. M., & Passarella, A. (2009). Energy Conservation in WSNs: a Survey, Elsevier Science Publishers. Ad Hoc Networks, 7(3), 537–568.
Ki Young Jang, Kyung Tae Kim, Hee Yong Youn, “An energy-efficient routing scheme for wireless sensor networks”, International Conference on Computational Science and Its Applications, ICCSA 2007.
Selvakumar, K., Sairamesh, L., & Kannan, A. (2017). An intelligent energy-aware secured algorithm for routing in wireless sensor networks. Wireless Personal Communications, 96(3), 4781–4798.
Sathiyavathi, V., Reshma, R., Saleema Parvin, S. B., SaiRamesh, L., & Ayyasamy, A. (2019). Dynamic Trust-Based Secure Multipath Routing for Mobile Ad-Hoc Networks. Intelligent Communication Technologies and Virtual Mobile Networks (pp. 618–625). Cham: Springer.
Chen, S., & Nahrstedt, K. (1999). Distributed Quality-of-Service Routing in Ad Hoc Networks. IEEE Journal On Selected Areas in Communications, 17(8), 1488–1505.
Zabin, F., Misra, S., Woungang, I., Rashvand, H. F., Ma, N.-W., & Ahsan Ali, M. (2008). REEP: data-centric, energy-efficient and reliable routing protocol for wireless sensor networks. IET Communications, 2, 995–1008.
Selvakumar, K., Sairamesh, L., & Kannan, A. (2019). Wise intrusion detection system using fuzzy rough set-based feature extraction and classification algorithms. International Journal of Operational Research, 35(1), 87–107.
Kamalanathan, S., Lakshmanan, S. R., & Arputharaj, K. (2017). Fuzzy-clustering-based intelligent and secured energy-aware routing. Handbook of Research on Fuzzy and Rough Set Theory in Organizational Decision Making (pp. 24–37). United States: IGI Global.
Murad, A. M., & Al-Mahadeen, B. (2007). Adding quality of service extensions to the enhanced associativity based routing protocol for Mobile Ad Hoc Networks (MANET). American Journal of Applied Sciences, 4, 876–881.
Yussof, S., & See, O. H. (2010). A Robust GA-based QoS Routing Algorithm for Solving Multi-constrained Path Problem. Journal of Computers, 5(9), 1322–1334.
Sinha, P., Sivakumar, R., & Bharghavan, V. (1999). CEDAR: A core extraction distributed ad hoc routing algorithm. IEEE Journal on Selected Areas in Communications, 17(8), 1454–1465.
Senthilkumar, M., Somasundaram, S., & Amuthakkannan, R. (2009). Power-aware multiple QoS constraints routing protocol with mobility prediction for MANET. The International Journal of Information Systems and Change Management, 4, 156–170.
Lian, J., L. Li and X. Zhu, "A multiple QoS constraints routing protocol based on mobile predicting in ad hoc network", Proceedings of IEEE International Conference on Wireless Communications, Networking and Mobile Computing, Shanghai, pp: 1608–1611, 2007.
Vinitha, A., and M. S. S. Rukmini. "Secure and energy-aware multi-hop routing protocol in WSN using taylor-based hybrid optimization algorithm." Journal of King Saud University-Computer and Information Sciences (2019).
Selvi, M., Thangaramya, K., Ganapathy, S., Kanagasabai Kulothungan, H., Nehemiah, K., & Kannan, A. (2019). An energy-aware trust-based secure routing algorithm for effective communication in wireless sensor networks. Wireless Personal Communications, 105(4), 1475–1490.
Zahedi, A., & Parma, F. (2019). An energy-aware trust-based routing algorithm using gravitational search approach in wireless sensor networks. Peer-to-Peer Netw. Appl., 12, 167–176.
Kavidha, V., & Ananthakumaran, S. (2019). Novel energy-efficient secure routing protocol for wireless sensor networks with mobile sink. Peer-to-Peer Network Application, 12, 881–892.
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Dhanalakshmi, B., SaiRamesh, L. & Selvakumar, K. Intelligent energy-aware and secured QoS routing protocol with dynamic mobility estimation for wireless sensor networks. Wireless Netw 27, 1503–1514 (2021). https://doi.org/10.1007/s11276-020-02532-8
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DOI: https://doi.org/10.1007/s11276-020-02532-8