Fuzzy Logic Based WSN with High Packet Success Rate and Security
Keywords:
Wireless Sensor Network, Fuzzy Inference System (FIS), Packet Delivery Ratio, Security of WSNAbstract
Considering the evidence that conditions accept a considerable place in each structure, owing to limited assets available at each sensor center, it is a difficult problem. Vitality safety is the primary concern in many remote sensor hub implementations. This is critical as the improvement in the device's lifetime depends primarily on restricting the usage of vitality in sensor hubs. The rationing and modification of vitality usage are of the most serious value in this context. In a remote sensor arrangement, the fundamental test is to schedule measurements for the least use of vitality. These classification frameworks are used to frame the classes in the structure and help efficiently use the strength that burdens out the network's lifespan. Besides, the degree of the center was taken into account in this work considering the measurement of cluster span as an improvement to the existing methods. The crucial piece of leeway of this suggested approach on affair clustering using fuzzy logic can increase the system's lifespan by reducing the problem area problem word.
References
N. Wang & L. Li “Shortest path routing with risk control for compromised wireless sensor networks”, IEEE Access, Vol. 7, pp. 19303-19311, 2019.
B. P. Deosarkar, N. S. Yadav, & R. P. Yadav, “Cluster head selection in clustering algorithms for wireless sensor networks: A survey”, International Conference on Computing, Communication and Networking, pp. 1-8, 2018.
K. Wu, & J. Harms “Multipath routing for mobile ad hoc networks”, Journal of communications and networks, Vol. 4, No. 1, pp. 48-58, 2002.
X. Wang, B. Moran, & M. Brazil “Hyperbolic positioning using RIPS measurements for wireless sensor networks”, IEEE International Conference on Networks, pp. 425-430, 2007.
E. Stavrou, & A. Pitsillides, “A survey on secure multipath routing protocols in WSNs”, Computer Networks, Vol. 54, No. 13, pp. 2215-2238, 2010.
Luo, Zhongqiang, C. Li, and L. Zhu. "A comprehensive survey on blind source separation for wireless adaptive processing: Principles, perspectives, challenges and new research directions”, IEEE Access, Vol. 6, pp: 66685-66708, 2018.
G. Zengen, Y. Schröder, S. Rottmann, F. Büsching, & L. C. Wolf “No-Cost distance estimation using standard WSN radios”, In IEEE INFOCOM 2016-The 35th Annual IEEE International Conference on Computer Communications, pp. 1-9, 2016.
J. S. Pan, T. T. Nguyen, T. K. Dao, T. S. Pan, & S. C. Chu “Clustering Formation in Wireless Sensor Networks: A Survey”, Journal of Network Intelligence, Vol. 2, No. 4, pp. 287-309, 2017.
Wankhade, Suchita R., and Nekita A. Chavhan. "A review on data collection method with sink node in wireless sensor network”, International Journal of Distributed and Parallel Systems, Vol. 4, No. 1, pp. 67-74, 2013.
W. Sambo, B. O. Yenke, A. Förster, P. Dayang “Optimized clustering algorithms for large wireless sensor networks: A review”, Sensors, Vol. 19, No. 2, pp. 3-22, 2019.
M. S. Sumalatha, and V. Nandalal. "An intelligent cross layer security based fuzzy trust calculation mechanism (CLS-FTCM) for securing wireless sensor network (WSN)." Journal of Ambient Intelligence and Humanized Computing, pp: 1-15, 2020.
F. Reza, and S. F. Bari. "A novel countermeasure technique to protect WSN against denial-of-sleep attacks using firefly and Hopfield neural network (HNN) algorithms." The Journal of Supercomputing, pp: 1-27, 2020.
A. A. Amod, M. Karyakarte, and H. Agrawal. "Post Quantum Security Solution for Data Aggregation in Wireless Sensor Networks." IEEE Wireless Communications and Networking Conference (WCNC), pp. 1-8, 2020.
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