Volume 13 , Issue 1 , PP: 9-22, 2021 | Cite this article as | XML | PDF | Full Length Article
S.Krishna Prabha 1 , Broumi said 2 , Selçuk Topal 3
Doi: https://doi.org/10.54216/IJNS.130102
Routers steer and bid network data, through packets that hold a variety of categories of data such as records, messages, and effortless broadcasts like web interface. The procedure of choosing a passageway for traffic in a network or between several networks is called routing. Starting from telephone networks to public transportation the principles of routing are applied. Routing is the higher-level decision making that directs network packets from their source en route for their destination through intermediate network nodes by specific packet forwarding mechanisms. The main function of the router is to set up optimized paths among the different nodes in the network. An efficient novel routing algorithm is proposed with the utilization of neutrosophic fuzzy logic in this work addition to many routing algorithms for finding the optimal path in the literature. In this approach, each router makes its own routing decision in the halting time. Various concepts like routing procedures, most expected vector, most expected object, and list of estimated delay are explained.
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Neutrosophic fuzzy set, Neutrosophic fuzzy routing, Generated Vector, Neutrosophic fuzzy vector, Most expected object, Neutrosophic most expected vector, Neutrosophic fuzzy list of estimated delay, internet of things.
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[1] R. E. Bellman, “Dynamic Programming”, NJ, Princeton University Press, 1957.
[2] L. Zadeh, “Fuzzy Sets”, Information and Control, 8, 338-353.1965.
[3] A. K. Dutta, A. R. W. Sait, “An Application of Intuitionistic Fuzzy in Routing Networks”, International Journal of Advanced Computer Science and Applications,Vol. 3, No.6, 2012.
[4] K. T. Atanassov, “Intuitionistic fuzzy sets”,Fuzzy Sets and Systems, 20, 87-96, 1986.
[5] F. Smarandache, “A Unifying Field in Logics: Neutrosophic Logic. Neutrosophy, Neutrosophic Set, Neutrosophic Probability”, American Research Press, Rehoboth, NM, 1999.
[6] D. Driankov, H. Hellendoorn, M. Reinfrank, “An Introduction to Fuzzy Control”, Springer-Verlag, Berlin, New York, 1993.
[7] S .Gayen, S. Jha, M. Singh, R.Kumar, “On a generalized notion of anti-fuzzy subgroup and some characterizations”, International Journal of Engineering and Advanced Technology, 8, 385-390, 2019.
[8] S. Gayen, F. Smarandache, S. Jha, R. Kumar, “Interval-valued neutrosophic subgroup based on interval-valued triple t-norm”, Neutrosophic sets in decision analysis and operations research; IGI Global, pp 215-243,2020.
[9] K. Wong, “Fuzzy routing control of service request messages in an individual computing environment”, Proc. of the 1995 ACM Symposium on Applied Computing, Nashville (USA), pp 548-551,1995.
[10] L. R. Ford, D.R. Fulkerson, “Flows in Networks”, Princeton,NJ; Princeton University Press, 1962.
[11] T. Mahmood, Q. Khan, K.Ullah, N.Jan, “Single Valued Neutrosophic Finite State Machine
and Switchboard State Machine”, ViXra, 2018.
[12] R. Kumar, A. Dey, S. Broumi, F.Smarandache, “A study of neutrosophic shortest path problem”,In Neutrosophic Graph Theory and Algorithms; IGI Global,148-179,2020.
[13] T. Mahmood , Q. Khan, M. A. Khan, “Q-Single Valued Neutrosophic Sets”, Journal of New Theory, 13 ,10-25,2016.
[14] R. Zhang, Y. A. Phillis, “Fuzzy Routing of Queueing Systems with Heterogeneous Servers”, Proc. of IEEE Intl. Conference on Robotics and Automation Albuquerque, New Mexico, pp. 2340-2345, April 1997.
[15] T. Mahmood, Q. Khan, “Interval neutrosophic finite switchboard state machine”, Afrika Matematika , 27 ,7-8 , 1361-1376, 2016.
[16] J. Pratihar, R. Kumar, A. Dey, S. Broumi, “Transportation problem in neutrosophic environment”, NeutrosophicGraph Theory and Algorithms;IGI Global, 180-212,2020.
[17] T. Mahmood, J. Ye, Q. Khan, “Vector similarity measures for simplified neutrosophic hesitant fuzzy set and their applications”, Journal of Inequalities and Special Functions, Volume 7, Issue 4,176-194, 2016.
[18] S. Upadhayay, M. Sharma, “Reinforcement of a new fuzzy mixed metric approach through fuzzy routing Algorithms”, IJCNS, 8,2, 271 – 276,2008.
[19] S. Pithani, A. S. Sethi, “A fuzzy Set Delay Representation for Computer Network Routing Algorithms”, Proc. Second Intl. Symposium on Uncertainty Modeling and Analysis, College Park, MD pp. 286-293, 1993.
[20] A. S. Tanenbaum, “Computer Networks”, Prentice-Hall, Englewood Cliffs, NJ, 1988.
[21] Gasim Alandjani and Eric. E.Johnson, “Fuzzy routing in Ad hoc networks”, IEEE, 2003.
[22] L. Barolli , A.Koyama ,T.Yamada, S. Yokoyama, “An Intelligent fuzzy routing scheme for improving ATM Network Performance using Violation tagging function”, IEEE Proceedings on Database and expert system application, pp. 5 -9, 2000.
[23] R. Kumar, S. A. Edalatpanah, H. Mohapatra, “Note on ''Optimal path selection approach for fuzzy reliable shortest path problem”, Journal of Intelligent & Fuzzy Systems (Preprint), pp.1-4, 2020.
[24] S. Broumi, M. Talea, A. Bakali et al., "Shortest path problem in fuzzy intuitionistic fuzzy and neutrosophic environment: an overview", Complex Intell. Syst., vol. 5, no. 4, pp. 371-378, 2019.
[25] S. Broumi, D. Nagarajan, A. Bakali et al., "The shortest path problem in interval valued trapezoidal and triangular neutrosophic environment", Complex Intell. Syst., vol. 5, no. 4, pp. 391-402, 2019.
[26] S. Broumi, A. Bakali, M. Talea et al., "Shortest path problem under interval valued neutrosophic setting", Int. J. Adv. Trends Comput. Sci. Eng., vol. 8, no. 1, pp. 216-222, 2019.
[27] R. Liu, “Study on single-valued neutrosophic graph with application in shortest path problem”, CAAI Transactions on Intelligence Technology, Vol. 5, Iss. 4, pp. 308–313, 2020.
[28] R. P. Tan, W.D. Zhang, S. Broumi, Solving methods for the shortest path problem based on trapezoidal fuzzy neutrosophic numbers. Control Decis, 34, pp. 851–860, 2019.
[29] L. Yang, D. Lin, R. P. Tan, Shortest Path Solution of Trapezoidal Fuzzy Neutrosophic Graph Based on Circle-Breaking Algorithm, Symmetry, 12(8), 1360, 2020 ; https://doi.org/10.3390/sym12081360.
[30] E. Çakır, Z. Ulukan, “A* Algorithm Under Single-Valued Neutrosophic Fuzzy Environment” In: Kahraman C., Cevik Onar S., Oztaysi B., Sari I., Cebi S., Tolga A. (eds) Intelligent and Fuzzy Techniques: Smart and Innovative Solutions. INFUS 2020. Advances in Intelligent Systems and Computing, vol 1197, 2021. Springer, Cham. http://doi-org-443.webvpn.fjmu.edu.cn/10.1007/978-3-030-51156-2_36.
[31] E. Çakır, Z. Ulukan, Bipolar Neutrosophic Fuzzy Dijkstra Algorithm and Its Application” In: Kahraman C., Cevik Onar S., Oztaysi B., Sari I., Cebi S., Tolga A. (eds) Intelligent and Fuzzy Techniques: Smart and Innovative Solutions. INFUS 2020. Advances in Intelligent Systems and Computing, vol 1197.,2021. Springer, Cham. http://doi-org-443.webvpn.fjmu.edu.cn/10.1007/978-3-030-51156-2_37.
[32] S. Broumi, M. Talea, A. Bakali, F. Smarandache, S. K. Patro, On the Neutrosophic Counterpart of Bellman-Ford Algorithm In: Ezziyyani M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2019). AI2SD 2019. Advances in Intelligent Systems and Computing, vol 1106, 2020. Springer, Cham. http://doi-org-443.webvpn.fjmu.edu.cn/10.1007/978-3-030-36677-3_13.
