Achieving maximum reliability in fault tolerant network design for variable networks

Applied Soft Computing Journal

Volumn 13, Issue 7, 2013, Pages 3211-3224

  Kaushik, B ^a   Kaur, N ^b   Kohli, A K ^c  

^a PTU   (India)

^b CGC   (India)

^c THAPAR UNIVERSITY   (India)

Author keywords

Fault tolerant optimal design; Fixed and varying link reliability; Maximizing reliability; Neural networks; Variable network size

Indexed keywords

FAULT TOLERANCE; NEURAL NETWORKS;

FAULT-TOLERANT NETWORKS; LINK RELIABILITY; NETWORK SIZE; NEURAL NETWORK METHOD; NOVEL NEURAL NETWORK; OPTIMAL DESIGN; OPTIMAL NETWORK DESIGN; RELIABILITY CALCULATION;

OPTIMIZATION;

EID: 84885682869     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2013.02.017     Document Type: Review

References (61)

1. A. Lendasse M.V. Wertz, Model selection with cross-validations and bootstraps application to time series prediction with RBFN models, in: Lecture Notes in Computer Science, Springer Berlin/Heidelberg, 2003, p. 2714.
2. Y.S. Dai, M. Xie, K.L. Poh, Modeling and analysis of correlated software failures of multiple types, IEEE Transactions on Reliability 54 (1) (2005) 100-106. (Pubitemid 40400318)
3. Y.S. Dai, M. Xie, Q. Long, S.H. Ng, Uncertainty analysis in software reliability modeling by Bayesian approach with maximum entropy principle, IEEE Transactions on Software Engineering 33 (11) (2007) 781-795. (Pubitemid 47595648)
4. Y.S. Dai, G. Levitin, Reliability and performance of tree-structured grid services, IEEE Transactions on Reliability 55 (2) (2006) 337-349. (Pubitemid 43905045)
5. Y.S. Dai, M. Xie, X. Wang, A heuristic algorithm for reliability modeling and analysis of grid systems, IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans 37 (2) (2007) 189-200. (Pubitemid 46477119)
6. Y.S. Dai, Y. Pan, X.K. Zou, A hierarchical modeling and analysis for grid service reliability, IEEE Transactions on Computers 56 (5) (2007) 681-691. (Pubitemid 46563348)
7. Y.S. Dai, G. Levitin, K.S. Trivedi, Performance and reliability of tree-structured grid services considering data dependence and failure correlation, IEEE Transactions on Computers 56 (7) (2007) 925-936. (Pubitemid 47249807)
8. T. Aven, Availability evaluation of oil gas-production and transportation systems, Reliability Engineering and System Safety 18 (1987) 35-44. (Pubitemid 17585562)
9. D.A. Savic, G.A. Walters, An evolution program for pressure regulation in water distribution networks, Engineering Optimization 24 (1995) 197-219.
10. K. Aggarwal, J. Gupta, K. Misra, A simple method for reliability evaluation of a communication system, IEEE Transactions on Communications 23 (5) (1975) 563-566.
11. K.K. Aggarwal, S. Rai, Reliability evaluation in computer-communication networks, IEEE Transactions on Reliability 30 (1981) 32-35.
12. S. Rai, A cutset approach to reliability evaluation in communication networks, IEEE Transactions on Reliability 1 (1982) 428-431. (Pubitemid 13488685)
13. J.S. Provan, M.O. Ball, The complexity of counting cuts and of computing the probability that a graph is connected, SIAM Journal of Computing 12 (1983) 777-788.
14. M.A. Samad, An efficient algorithm for simultaneously deducing minimal paths as well as cuts of a communication-network, Microelectronics and Reliability 27 (1987) 437-441. (Pubitemid 17634433)
15. G. Chaudhuri, K. Hu, N. Afshar, A new approach to system reliability, IEEE Transactions on Reliability 50 (1) (2001) 75-84. (Pubitemid 32736749)
16. T. Jin, D.W. Coit, Approximating network reliability estimates using linear and quadratic unreliability of minimal cuts, Reliability Engineering and System Safety 82 (2003) 41-48.
17. W.J. Ke, S.D. Wang, Reliability evaluation for distributed computing networks with imperfect nodes, IEEE Transactions on Reliability 46 (3) (1997) 342-349.
18. P. Doulliez, E. Jalnoulle, Transportation network with random arc capacities, RAIRO-Operations Research 3 (1972) 45-60.
19. S. Lolas, O.A. Olatunbosun, Prediction of vehicle reliability performance using artificial neural networks, Expert Systems with Applications 34 (2008) 2360-2369. (Pubitemid 351173747)
20. J.B. Cardoso, Structural reliability analysis using Monte Carlo simulation and neural networks, Advances in Engineering Software 39 (2008) 505-513. (Pubitemid 351200030)
21. J.E. Hurtado, D.A. Alvarez, An optimization method for learning statistical classifiers in structural reliability, Probablistic Engineering Mechanics 25 (2009) 26-34.
22. W.-C. Yeh, Y.-C. Lin, Y.Y. Chung, M. Chih, A particle swarm optimization approach based on Monte Carlo simulation for solving the complex network reliability problem, IEEE Transactions on Reliability 59 (1) (2010) 212-221.
23. E. Inohira, H. Yokoi, An optimal design method for artificial NN by the DOE method, Journal of Advanced Computational Intelligence and Intelligent Informatics 11 (6) (2007) 593-594.
24. B. Kaushik, N. Kaur, A.K. Kohli, A new ANN method for measuring overall reliability and performance in growing computer networks with static and variable connections, International Journal of Computer Science and Communication 2 (1) (2011) 79-87.
25. B. Kaushik, N. Kaur, A.K. Kohli, An optimized ANN design for measuring overall reliability for growing computer networks with fixed and varying links, International Journal of Computational Engineering & Management 11 (2011) 12-21.
26. B. Kaushik, N. Kaur, A.K. Kohli, A computational study on the design of overall reliability measures of optimized ANN for computer networks with fixed and varying link reliabilities, in: IEEE Explore 2011, 2011.
27. B. Kaushik, N. Kaur, A.K. Kohli, A new method for measuring overall reliability and performance in growing computer networks with static and variable connections, International Journal of Computer Technology & Applications 2 (1) (2011) 1-14.
28. B. Kaushik, N. Kaur, A.K. Kohli, An enhanced ANN approach for optimizing design of highly reliable variable sized computer networks, Journal of Artificial Intelligence 2 (2011) 31-41.
29. A.N. Venetsanopoulos, I. Singh, Topological optimization of communication networks subject to reliability constraints, Problems of Control and Information Theory 15 (1986) 63-78. (Pubitemid 16555833)
30. C.S. Ratana, A.E. Smith, Estimation of all-terminal network reliability using an artificial neural network, Computers and Operations Research 29 (7) (1999) 1-28.
31. C. Srivaree-ratana, A. Konak, A.E. Smith, Estimation of all-terminal network reliability using an artificial neural network, Computers and Operations Research 29 (7) (2002) 849-868. (Pubitemid 34135094)
32. F. Altiparmak, B. Dengiz, A.E. Smith, A general neural network model for estimating telecommunication network reliability, IEEE Transactions on Reliability 58 (1) (2009) 2-9.
33. D.W. Coit, A.E. Smith, Reliability optimization of series-parallel systems using a genetic algorithm, IEEE Transactions on Reliability 45 (2) (1996) 254-260.
34. B. Dengiz, F. Altiparmak, A.E. Smith, Local search genetic algorithm for optimal design of reliable networks, IEEE Transactions on Evolutionary Computation 1 (3) (1997) 179-188. (Pubitemid 127771027)
35. B. Dengiz, F. Altiparmak, A.E. Smith, Efficient optimization of all-terminal reliable networks using an evolutionary approach, IEEE Transactions on Reliability 46 (1997) 18-26. (Pubitemid 127762144)
36. J. Kennedy, R.C. Eberhart, Particle swarm optimization, in: IEEE International Conference on Neural Networks, 1995, pp. 1942-1948.
37. G. Levitin, X.H. Hu, Y.S. Dai, Particle swarm optimization in reliability engineering, in: International Conference on Computational Intelligence in Reliability Engineering, 2006, pp. 83-112.
38. M.K. Pandey, M.K. Tiwari, M.J. Zuo, Interactive enhanced particle swarm optimization: a multi-objective reliability application, Journal of Risk and Reliability 221 (3) (2007) 177-191.
39. W.C. Yeh, A two-stage discrete particle swarm optimization for the problem of multiple multi-level redundancy allocation in series systems, Expert Systems with Applications 36 (5) (2009) 9192-9200.
40. O. Dengiz, A. Konak, A.E. Smith, Connectivity management in mobile ad hoc networks using particle Swarm optimization, Ad Hoc Networks 9 (2011) 1312-1326.
41. C.J. Colbourn, The Combinatorics of Network Reliability, Oxford, New York, 1987.
42. D.R. Shier, Network Reliability and Algebraic Structure, Oxford, New York, 1991.
43. I. Gertsbakh, Reliability Theory, Springer-Verlag, Berlin, Heidelberg, Germany, 2000.
44. S.J. Kamat, M.W. Riley, Determination of reliability using event based Monte Carlo simulation, IEEE Transactions on Reliability 24 (1) (1975) 73-75.
45. S.J. Kamat, W.E. Franzmeier, Determination of reliability using event-based Monte Carlo simulation, Part 2, IEEE Transactions on Reliability 25 (3) (1976) 254-255.
46. G.S. Fishman, A Monte Carlo sampling plan for estimating network reliability, Operations Research 34 (1986) 81-594.
47. P. Kubat, Estimation of reliability for communication/computer networks simulation/ analytical approach, IEEE Transactions on Communications 37 (9) (1989) 927-933. (Pubitemid 20618613)
48. T.L. Landers, H.A. Taha, C.L. King, A reliability simulation approach for use in the design process, IEEE Transactions on Reliability 40 (2) (1991) 177-181.
49. J.Y. Lin, C.E. Donaghey, Monte Carlo simulation to determine minimal cut sets and system reliability, in: Proceedings of Annual Reliability and Maintainability Symposium, 1993.
50. H. Wang, H. Pham, Survey of reliability and availability evaluation of complex networks using Monte Carlo techniques, Microelectronics and Reliability 37 (2) (1997) 187-209. (Pubitemid 127421729)
51. S.R.V. Majety, M. Dawande, J. Rajgopal, Optimal reliability allocation with discrete cost-reliability data for components, Operations Research 47 (6) (1999) 899-906. (Pubitemid 30594272)
52. W.C. Yeh, A MCS-RSM approach for network reliability to minimize the total cost, International Journal of Advanced Manufacturing Technology 22 (2003) 681-688.
53. Y. Shpungin, Networks with unreliable nodes and edges: Monte Carlo lifetime estimation, World Academy of Science, Engineering and Technology 27 (2007) 349-354.
54. H.K. Stinchcombe, H. White M., Multilayer feed forward networks are universal approximators, Neural Networks 2 (3) (1989) 59-66.
55. H. White, Connectionist nonparametric regression: multilayer feed forward networks can learn arbitrary mappings, Neural Networks 3 (5) (1990) 35-49.
56. S. Geman, E. Bienenstock, R. Doursat, Neural networks and the bias/variance dilemma, Neural Computation 4 (1992) 1-58.
57. B. Cheng, D.M. Titterington, Neural networks: a review from a statistical perspective, Statistical Science 9 (1994) 2-54.
58. K. Mehrotra, C.K. Mohan, S. Ranka, Elements of Artificial Neural Networks, MIT Press, MA, USA, 1996, pp. 65-106 (Chapter 3).
59. F. Karray, C.D. Silva, Soft Computing and Intelligent Systems Design-Theory, Tools and Applications, Addison Wesley, 2004, pp. 249-293 (Chapter 5).
60. S. Rajasekran, V. Pai, Neural Networks, Fuzzy Logic, and Genetic Algorithms Synthesis and Applications, PHI, New Delhi, India, 2005, pp. 34-86 (Chapter 3).
61. Neuralworks: Reference Guide and Software. NeuralWare, Pittsburgh, PA, Various Years. 〈http://www.neuralware.com〉.