A General Neural Network Model for Estimating Telecommunications Network Reliability

This paper puts forth a new encoding method for using neural network models to estimate the reliability of telecommunications networks with identical link reliabilities. Neural estimation is computationally speedy, and can be used during network design optimization by an iterative algorithm such as tabu search, or simulated annealing. Two significant drawbacks of previous approaches to using neural networks to model system reliability are the long vector length of the inputs required to represent the network link architecture, and the specificity of the neural network model to a certain system size. Our encoding method overcomes both of these drawbacks with a compact, general set of inputs that adequately describe the likely network reliability. We computationally demonstrate both the precision of the neural network estimate of reliability, and the ability of the neural network model to generalize to a variety of network sizes, including application to three actual large scale communications networks.

[1]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[2]  Yen-Tseng Hsu,et al.  Fault modeling and reliability evaluations using artificial neural networks , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[3]  Alice E. Smith,et al.  Efficient optimization of all-terminal reliable networks, using an evolutionary approach , 1997 .

[4]  Alice E. Smith,et al.  Reliability estimation of computer communication networks: ANN models , 2003, Proceedings of the Eighth IEEE Symposium on Computers and Communications. ISCC 2003.

[5]  V. Miranda,et al.  Composite Reliability Assessment Based on Monte Carlo Simulation and Artificial Neural Networks , 2007, IEEE Transactions on Power Systems.

[6]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[7]  Bo Li,et al.  A dynamic RWA algorithm in a wavelength-routed all-optical network with wavelength converters , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[8]  Michael Ball,et al.  Backtracking Algorithms for Network Reliability Analysis , 1977 .

[9]  Rong-Hong Jan.  Design of reliable networks , 1992, [Conference Record] SUPERCOMM/ICC '92 Discovering a New World of Communications.

[10]  Xiangjian He,et al.  A New Universal Generating Function Method for Estimating the Novel Multiresource Multistate Information Network Reliability , 2010, IEEE Transactions on Reliability.

[11]  Abdullah Konak,et al.  Estimation of all-terminal network reliability using an artificial neural network , 2002, Comput. Oper. Res..

[12]  Zhou Zhongding,et al.  A synthetic evaluation methodology based on neural networks theory for reliability indexes of communication networks , 2001, 2001 International Conferences on Info-Tech and Info-Net. Proceedings (Cat. No.01EX479).

[13]  D. DouglasE.Torres,et al.  Reliability assessment of complex networks using rules extracted from trained ANN and SVM models , 2005, Fifth International Conference on Hybrid Intelligent Systems (HIS'05).

[14]  D.E.D. Torres,et al.  Reliability assessment of complex networks using rules extracted from trained ANN and SVM models , 2005 .

[15]  Ahmad Khademzadeh,et al.  Backup path set selection in ad hoc wireless network using link expiration time , 2008, Comput. Electr. Eng..

[16]  Wei-Chang Yeh,et al.  Evaluate Voting System Reliability Using the Monte Carlo simulation and Artificial Neural Network , 2007, The 2nd International Conference on Wireless Broadband and Ultra Wideband Communications (AusWireless 2007).

[17]  Suresh Subramaniam,et al.  Loopback recovery from double-link failures in optical mesh networks , 2004, IEEE/ACM Transactions on Networking.

[18]  Lars Kai Hansen,et al.  Neural Network Ensembles , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  K. R. Venugopal,et al.  A heuristic for placement of limited range wavelength converters in all-optical networks , 1999, IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320).

[20]  Ravindra K. Ahuja,et al.  Network Flows , 2011 .

[21]  Charles J. Colbourn,et al.  Bounding all-terminal reliability in computer networks , 1988, Networks.

[22]  Kurt Hornik,et al.  Multilayer feedforward networks are universal approximators , 1989, Neural Networks.

[23]  A. Snow,et al.  Assessing dependability of wireless networks using neural networks , 2005, MILCOM 2005 - 2005 IEEE Military Communications Conference.

[24]  Elie Bienenstock,et al.  Neural Networks and the Bias/Variance Dilemma , 1992, Neural Computation.

[25]  George Cybenko,et al.  Approximation by superpositions of a sigmoidal function , 1992, Math. Control. Signals Syst..

[26]  I. Gertsbakh,et al.  A NEW MONTE CARLO METHOD FOR ESTIMATING EQUILIBRIUM NETWORK RELIABILITY PARAMETERS T. Elperin, I.Gertsbakh, M. Lomonosov , 2022 .

[27]  C.-C. Wu,et al.  An improved neural network realization for reliability analysis , 1998 .

[28]  Alice E. Smith,et al.  Local search genetic algorithm for optimal design of reliable networks , 1997, IEEE Trans. Evol. Comput..

[29]  Alice E. Smith,et al.  Optimal Design of Reliable Computer Networks: A Comparison of Metaheuristics , 2003, J. Heuristics.

[30]  J. Scott Provan,et al.  The Complexity of Counting Cuts and of Computing the Probability that a Graph is Connected , 1983, SIAM J. Comput..

[31]  Ravindra K. Ahuja,et al.  Network Flows: Theory, Algorithms, and Applications , 1993 .

[32]  David W. Coit,et al.  Solving the redundancy allocation problem using a combined neural network/genetic algorithm approach , 1996, Comput. Oper. Res..

[33]  Mamoun Suliman,et al.  Neural network for the reliability analysis of simplex systems , 1990 .

[34]  Alice E. Smith,et al.  Bias and variance of validation methods for function approximation neural networks under conditions of sparse data , 1998, IEEE Trans. Syst. Man Cybern. Part C.

[35]  R. Wilkov,et al.  Analysis and Design of Reliable Computer Networks , 1972, IEEE Trans. Commun..

[36]  G. S. Sekhon,et al.  An artificial neural network for modeling reliability, availability and maintainability of a repairable system , 2006, Reliab. Eng. Syst. Saf..

[37]  Richard M. Van Slyke,et al.  Network reliability analysis: Part I , 1971, Networks.