Neural Networks for Shortest Path Computation and Routing in Computer Networks

IEEE Transactions on Neural Networks

Volumn 4, Issue 6, 1993, Pages 941-954

  Mehmet Ali, Mustafa K ^a   Kamoun, Faouzi ^a  

^a Dept of Electrical and Computer Engineering   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL METHODS; DISTRIBUTED DATABASE SYSTEMS; NEURAL NETWORKS; OPTIMIZATION; PACKET SWITCHING;

CONSTRAINED OPTIMIZATION; NETWORK ROUTING; SHORTEST PATH COMPUTATION;

COMPUTER NETWORKS;

EID: 0027703186     PISSN: 10459227     EISSN: 19410093     Source Type: Journal    
DOI: 10.1109/72.286889     Document Type: Article

References (21)

1. M. Schwartz, Telecommunication Networks: Protocols, Modeling and Analysis. Reading, MAoe: Addison-Wesley, 1987.
2. J. J. Hopfield, “Neural networks and physical systems with emergent collective computational abilities,” Proc. Nat. Acad. Sci., vol. 79, pp. 2554–2558, 1982.
3. J. J. Hopfield and D. W. Tank, “'Neural' computations of decisions in optimization problems,” Biol. Cybern., vol. 52, pp. 141–152, 1986.
4. D. W. Tank and J. J. Hopfield, “Simple 'Neural' optimization networks: An A/D converter, signal decision circuit, and a linear programming circuit,” IEEE Trans. Circuits. Syst., vol. CAS-33, no. 5, pp. 533–541, 1986.
5. J. J. Hopfield, “Neurons with graded response have collective computational properties like those of two state neurons,” Proc. Nat. Acad. Sci., vol. 81, pp. 3088–3092, 1984.
6. D. P. Berteskas and R. G. Gallager, Data Networks. Englewood Cliffs, NJ: Prentice-Hall, 1987.
7. H. E. Rauch and T. Winarske, “Neural networks for routing communication traffic,” IEEE Cont. Syst. Mag., pp. 26–30, Apr. 1988.
8. L. Zhang and S. C. A. Thomopoulos, “Neural network implementation of the shortest path algorithm for traffic routing in communication networks,” in Proc. Int. Joint Conf. Neural Networks, June 1989, p. II. 591.
9. A. Moopenn, A. P. Thakoor, and T. Duong, “A neural network for Euclidean distance minimization,” in Proc. IEEE Int. Conf. Neural Networks, 1988, II.349-356.
10. P. W. Protzel, “Comparative performance measure for neural networks solving optimization problems,” iujjn Proc. Int. Joint Conf. Neural Networks, 1990, H.523-526.
11. R. D. Brandt et al, “Alternative networks for solving the traveling salesman problem and the list-matching problem,” in Proc. IEEE Int. Conf Neural Networks, 1988, pp. II. 333–340.
12. A. Moopenn, T. Duong, and A. P. Thakoor, “Digital-analog hybrid synapse chips for electronic neural networks,” in Advances in Neural Information Processing Systems, vol. 2, D. S. Touretzky, Ed. Morgan Kaufmann, 1990, pp. 769–776.
13. V. Wilson and G. S. Pawley, “On the stability of the TSP problem algorithm of Hopfield and Tank,” Biol. Cybern., vol. 58, pp. 63–70, 1988.
14. A. Kahng, “Traveling salesman heuristics and embedding dimension in the Hopfield model,” in Proc. IJCNN, vol. I, 1989, pp. 513–520.
15. L. Kleinrock, Communication Networks: Stochastic Message Flow and Delay. New York: McGraw-Hill, 1964.
16. L. Fratta, M. Gerla, and L. Kleinrock, “The flow deviation method: An approach to store and forward communication network design,” Networks, vol. 3, pp. 97–133, 1973.
17. D. G. Cantor and M. Gerla, “Optimum routing in a packet switch computer network,” IEEE Trans. Commun., vol. COM-23, no. 10, pp. 1062–1069, 1974.
18. M. Schwartz and C. K. Cheung, “The gradient projection algorithm for multiple routing in message switched systems,” IEEE Trans. Commun., vol. COM-24, no. 4, pp. 449–456, 1976.
19. J. F. Hayes, Modeling and Analysis of Computer Communications Networks. New York: Plenum, 1984.
20. P. J. Courtois and P. Semal, “A flow assignment algorithm based on the flow deviation method,” in Proc. ICCC 1980, pp. 77–83.
21. M. Takeda and J. W. Goodman, “Neural networks for computation: Number representations and programming complexity,” Appl. Opt., vol. 25, no. 18, pp. 3033–3046, 1986.