Abstract
Wireless Sensor Networks are categorized by the improved energy consumption parameters. The nodes are deployed in challenging surroundings and they are not communicated for a long time with lacking of energy level. These kinds of nodes will be the victim of security attacks, the conciliation nodes are guided all the data packets send to the base station of the network. In this paper proposes, The Fuzzy-based Secured Authentication and Clustering (FSAC) Algorithm observes the different kinds of the data packets transmitted within the sensors to avoid the attacks. The FSAC is implemented to use the proficient routing path to diminish the energy consumption. This method finds the adjacent transmitting node to improve the proficient path setup for the data packet routing using the fuzzy logic method. The simulation results specify that the proposed method increases the energy up to 12% compared to the related methods.
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References
Djenouri, D., & Bagaa, M. (2017). Energy-aware constrained relay node deployment for sustainable wireless sensor networks. IEEE Transactions on Sustainable Computing,2(1), 30–42.
Manjeshwar, A., & Agrawal, D. P. (2001). TEEN: A routing protocol for enhanced efficiency in wireless sensor networks. In Null (p. 30189a). IEEE.
Getu, T. M., Ajib, W., & Yeste-Ojeda, O. A. (2017). Tensor-based efficient multi-interferer RFI excision algorithms for SIMO systems. IEEE Transactions on Communications,65(7), 3037–3052.
Wang, Z., Zhang, L., Zheng, Z., & Wang, J. (2018). Energy balancing RPL protocol with multipath for wireless sensor networks. Peer-to-Peer Networking and Applications,11(5), 1085–1100.
Nguyen, T. G., So-In, C., Nguyen, N. G., & Phoemphon, S. (2017). A novel energy-efficient clustering protocol with area coverage awareness for wireless sensor networks. Peer-to-Peer Networking and Applications,10(3), 519–536.
Kumar, D. (2013). Performance analysis of energy efficient clustering protocols for maximising lifetime of wireless sensor networks. IET Wireless Sensor Systems,4(1), 9–16.
Zakariayi, S., & Babaie, S. (2019). DEHCIC: A distributed energy-aware hexagon based clustering algorithm to improve coverage in wireless sensor networks. Peer-to-Peer Networking and Applications, 12(4), 689–704.
Gholami, M., & Panahi, A. (2014). Enhancing nodes lifetime optimum protocol for dissemination of information in WSN. International Journal of Computers Communications & Control,9(3), 276–283.
Lee, H., Jang, M., & Chang, J. W. (2014). A new energy-efficient cluster-based routing protocol using a representative path in wireless sensor networks. International Journal of Distributed Sensor Networks,10(7), 527928.
Farooq, M. O., Dogar, A. B., & Shah, G. A. (2010). MR-LEACH: Multi-hop routing with low energy adaptive clustering hierarchy. In 2010 fourth international conference on sensor technologies and applications (SENSORCOMM) (pp. 262–268). IEEE.
Khelifi, M., & Djabelkhir, A. (2012). LMEEC: Layered multi-hop energy efficient cluster-based routing protocol for wireless sensor networks. Preprint arXiv:1201.0725.
Yoon, M., Kim, Y. K., & Chang, J. W. (2013). An energy-efficient routing protocol using message success rate in wireless sensor networks. JoC,4(1), 15–22.
Saini, P., & Sharma, A. K. (2010). Energy efficient scheme for clustering protocol prolonging the lifetime of heterogeneous wireless sensor networks. International Journal of Computer Applications,6(2), 30–36.
Lindsey, S., & Raghavendra, C. S. (2002). PEGASIS: Power-efficient gathering in sensor information systems. In Aerospace conference proceedings, 2002. IEEE (Vol. 3, pp. 3–3). IEEE.
Nikolidakis, S. A., Kandris, D., Vergados, D. D., & Douligeris, C. (2013). Energy efficient routing in wireless sensor networks through balanced clustering. Algorithms,6(1), 29–42.
Saravanan, T., Saritha, G., & Srinivsan, V. (2014). A analysis of flat routing protocols in sensor N/W. Middle-East Journal of Scientific Research,20(12), 2566–2570.
Tam, N. T., Hai, D. T., Son, L. H., & Vinh, L. T. (2018). Improving lifetime and network connections of 3D wireless sensor networks based on fuzzy clustering and particle swarm optimization. Wireless Networks,1–14, 1477–1490.
Ha, Y. G., Kim, H., & Byun, Y. C. (2012). Energy-efficient fire monitoring over cluster-based wireless sensor networks. International Journal of Distributed Sensor Networks,8(2), 460754.
Yong, Z., & Pei, Q. (2012). A energy-efficient clustering routing algorithm based on distance and residual energy for wireless sensor networks. Procedia Engineering,29, 1882–1888.
Sarkar, A., & Murugan, T. S. (2017). Cluster head selection for energy efficient and delay-less routing in wireless sensor network. Wireless Networks,1–18, 303–320.
Mao, X., Tang, S., & Li, X.-Y. (2011). Energy efficient opportunistic routing in wireless sensor networks. IEEE Transactions and Parallel and Distributed System,15(2), 551–591.
Zhan, G., & Shi, W. (2011). Design and Implementation of TARF: A trust aware routing framework for wireless sensor networks. IEEE Transactions on Dependable and Secure Computing,9(2), 184–197.
Li, Q., & Gao, G. (2012). Mitigating routing misbehavior in disruption tolerant networks. IEEE Transactions on Information Forensics and Security,7(2), 664–675.
Lee, J.-S., & Cheng, W.-L. (2012). Fuzzy-logic-based clustering approach for wireless sensor networks using energy predication. IEEE Sensors Journal,12(9), 2891–2897.
Ahvar, E., Pourmoslemi, A., & Piran, M. J. (2011). FEAR: A fuzzy-based energy-aware routing protocol for wireless sensor networks. arXiv preprint arXiv:1108.2777.
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.
AlMomani, I. M., & Saadeh, M. K. (2011). FEAR: Fuzzy-based energy aware routing protocol for wireless sensor network. Int’I of Communications, Network and System Sciences,4, 403–415.
Athmani, S., Bilami, A., & Boubiche, D. E. (2017). EDAK: An efficient dynamic authentication and key management mechanism for heterogeneous WSNs. Future Generation Computer Systems,92, 789–799.
Gaber, T., Abdelwahab, S., Elhoseny, M., & Hassanien, A. E. (2018). Trust-based secure clustering in WSN-based intelligent transportation systems. Computer Networks,146, 151–158.
Zhou, J. (2013). Efficient and secure routing protocol based on encryption and authentication for wireless sensor networks. International Journal of Distributed Sensor Networks,2013, 17.
Zhu, S., Setia, S., & Hahidua, S. (2003). LEAP: Efficient security mechanisms for large-scale distributed sensor networks. In Proceedings of the 10th ACM conference on computer and communications security (pp. 62–72), ACM.
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Sureshkumar, C., Sabena, S. Fuzzy-Based Secure Authentication and Clustering Algorithm for Improving the Energy Efficiency in Wireless Sensor Networks. Wireless Pers Commun 112, 1517–1536 (2020). https://doi.org/10.1007/s11277-020-07113-8
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DOI: https://doi.org/10.1007/s11277-020-07113-8