Abstract
In communication networks (CNs), the uncertainty is caused by the dynamic nature of the traffic demands. Therefore there is a need to incorporate the uncertainty into the network bandwidth capacity design. For this purpose, this paper developed a fuzzy methodology for network bandwidth design under demand uncertainty. This methodology is usually used for offline traffic engineering optimization, which takes a centralized view of bandwidth design, resource utilization, and performance evaluation. In this proposed methodology, uncertain traffic demands are first handled into a fuzzy number via a fuzzification method. Then a fuzzy optimization model for the network bandwidth allocation problem is formulated with the consideration of the trade-off between resource utilization and network performance. Accordingly, the optimal network bandwidth capacity can be obtained by maximizing network revenue in CNs. Finally, an illustrative numerical example is presented for the purpose of verification.
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References
L. Yu, W. Yue, and S. Wang, Network bandwidth design under uncertainty, Memoirs of Konan University, Intelligence & Informatics Series, 2008, 1(1): 91–98.
J. Wu, W. Yue, and S. Wang, Stochastic model and analysis for capacity optimization in communication network, Computer Communications, 2006, 29(12): 2377–2385.
D. Mitra and Q. Wang, Stochastic traffic engineering for demand uncertainty and risk-aware network revenue management, IEEE Transactions on Networks, 2005, 13(2): 221–233.
D. Mitra and K. Ramakrishnan, A case study of multiservice multipriority traffic engineering design for data networks, in Proc. IEEE GLOBECOM, 1999, 1077–1083.
S. Suri, M. Waldvogel, D. Bauer, and P. Warkhede, Profile-based routing and traffic engineering, Computer Communications, 2003, 26(4): 351–365.
K. Meesublak, Network design under demand uncertainty, Doctoral Dissertation, University of Pittsburgh, USA, 2009.
D. Mitra and Q. Wang, Stochastic traffic engineering with applications to network revenue management, in Proc. IEEE INFOCOM, 2001, 1300–1309.
D. Mitra and Q. Wang, Risk-aware network profit management in a two-tier market, in Proc. 18th International Teletraffic Congress, 2003.
J. Wu, W. Yue, and S. Wang, Stochastic traffic engineering design and optimization for multimedia communication networks, IEICE Technical Report, 2005, 104(564): 19–24.
J. Wu, W. Yue, and S. Wang, Optimization of bandwidth allocation in communication networks with penalty cost, Lecture Notes in Computer Science, 2005, 3516: 539–547.
D. Dubois and H. Prade, Evaluating Consumer Loans Using Neural Networks, Academic Press, New York, 1980.
L. Li, S. N. Kabadi, and K. P. K. Nair, Fuzzy models for single-period inventory problem, Fuzzy Sets and Systems, 2002, 112(3): 273–289.
S. J. Chen and C. L. Hwang, Fuzzy Multiple Attribute Decision Making: Methods and Applications, Springer-Verlag, Berlin, 1992.
R. R. Yager, A procedure for ordering fuzzy subsets of the unit interval, Information Sciences, 1981, 24(2): 143–161.
T. S. Liou and M. J. Wang, Ranking fuzzy numbers with integral values, Fuzzy Sets and Systems, 1992, 50(3): 247–255.
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This work is partially supported by the grants from the National Natural Science Foundation of China, the Knowledge Innovation Program of the Chinese Academy of Sciences, and the GRANT-IN-AID FOR SCIENTIFIC RESEARCH (No. 19500070) and MEXT.ORC (2004–2008), Japan.
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Yu, L., Yue, W. & Wang, S. Fuzzy-based network bandwidth design under demand uncertainty. J Syst Sci Complex 23, 61–70 (2010). https://doi.org/10.1007/s11424-010-9272-5
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DOI: https://doi.org/10.1007/s11424-010-9272-5