Minimize Delay and High PDR of Wireless Sensor Network using Cluster based Routing Protocol
Keywords:
Wireless Sensor Network, Fuzzy Logic System, Packet Delivery Ratio, Dead Node, EnergyAbstract
Wireless Sensor Network (WSN) have been advanced to give a superior administrations, among them WSNs have developed as a potential innovation that pulled in expanding consideration and sending as a superior and minimal effort answer for last-mile broadband Web get to. WMNs comprise of work switches and work customers. WSN is a promising remote innovation for a few developing and industrially fascinating applications, e.g., broadband home systems administration, network and neighborhood systems, facilitated arrange the executives, canny transportation frameworks. It is picking up noteworthy consideration as a conceivable route for Internet specialist organizations (ISPs) and opposite end clients to build up vigorous and solid remote broadband administration access at a sensible expense. This paper present dynamic cluster head selection (DCHS) network and used to fuzzy inference system (FIS) technique. The proposed technique is best performance compared to previous one.
References
Rohit Pachlor and Deepti Shrimanikar, “LAR-CH: A Cluster-Head Rotation Approach for Sensor networks”, IEEE Sensors Journal, Volume 18, Issue 23, pp. No. 01-08, Dec.1, 2018.
M. Bheemalingaiah and M. M. Naidu, “Performance Analysis of Power-aware Node-disjoint Multipath Source Routing in Mobile Ad Hoc Networks”, IEEE 7th International Advance Computing Conference, pp. No. 361-371, IEEE 2017.
Dogan Yildiz, Serap Karagol and Okan Ozgonelen, “A Hyperbolic Location Algorithm for Various Distributions of a Wireless Sensor Networks”, Smart Grid and Cities Congress and Fair (ICSG), 5th International Istanbul, pp. No. 451-459, IEEE 2016.
Alexandros Ladas, Nikolaos Pavlatos, Nuwan Weerasinghe and Christos Politis, “Multipath Routing Approach to Enhance Resiliency and Scalability in Ad-hoc Networks”, Ad-hoc and Sensor Networking Symposium, PP. No.01-06, IEEE 2016.
Pengwu Wan, Benjian Hao, Zan Li, Licun Zhou, Mian Zhang, “Time differences of arrival estimation of mixed interference signals using blind source separation based on wireless sensor networks”, IET Signal Processing, vol.10, issue 8, pp. 924-929, 2016.
Mohammad K., Alavi O., Mostafaeipour A., Goudarzi N. and Jalilv M., “Assessing different parameters estimation methods of Weibull distribution to compute wind power density”, ELSE VIER Energy Conversion and Management Journal, Vol.108, pp. 322-335, 2016.
Miriam Carlos-Mancilla, Ernesto López-Mellado, and Mario Siller, “Wireless Sensor Networks Formation: Approaches and Techniques”, Journal of Sensors, vol. 2016, Article ID 2081902, 18 pages, 2016.
Park S. Y. and Lee J. J., “Stochastic Opposition-Based Learning Using Beta Distribution in Differential Evolution”, IEEE Transactions On Cybernetics, vol. 46, Number 10, pp. 2184-2194, October 2016.
Osama Ennassr, Guoliang Xing and Xiaobo Tan, “Distributed Time-Difference-of-Arrival (TDOA)-based Localization of a Moving Target”, in Proc. IEEE 58th Conference on Decision and Control (CDC), pp. 2652-2658, IEEE 2016.
Santar Pal Singh, S.C. Sharma, “Range-Free Localization Techniques in Wireless Sensor Networks: A Review”, in Proc. 3rd International Conference on Recent Trends in Computing 2015 (ICRTC-2015), vol.57, pp. 7–16, 2015.
Yildiz D., Karagol S., Ozgonelen O., Tadiparthi S., Bidaksh M. N., “A Novel Self Localization Approach for Sensors”, Sensor Signal Processing for Defense (SSPD), Edinburgh, Scotland, 2015.
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