QoS Routing Algorithm Using Competitive PCNN

Abstract:

Article Preview

The solution of the multi-constrained QoS routing is translated into a shortest path problem for a weighted graph, and the problem of multi-constrained QoS routing is successfully solved using the properties of pulse wave parallel propagation of the competitive PCNN. The number of iteration of our algorithm is dependent of the length of the globally optimal multi-constrained QoS routing between source node and destination node and independent of the number of nodes and edges and the complexity of network distribution structure. The method shows better computational performance and dominance and has important significance in both theory and applications.

Info:

Periodical:

Edited by:

Mohamed Othman

Pages:

1908-1912

Citation:

D. M. Zhou and H. Cai, "QoS Routing Algorithm Using Competitive PCNN", Applied Mechanics and Materials, Vols. 229-231, pp. 1908-1912, 2012

Online since:

November 2012

Export:

Price:

$38.00

[1] J.F. Jiang, R.F. Cheng, X.Y. Tang et al. A multiple constrained QoS routing based on immune-ant algorithm. Journal of China Institute of Communications, Vol. 25(8) (2004) pp.89-95. (in Chinese).

[2] J.F. Jiang, X.Y. Tang. A Multiple constrained QoS routing selection based on immune genetic algorithm. Computer Simulation, Vol. 21(3) (2004) pp.11-54. (in Chinese).

[3] J.Y. Dong, J.Y. Zhang. Multi-constrained routing algorithm based on accumulating competition neural networks. Control and Decision, Vol. 19(7) (2004) pp.751-755. (in Chinese).

[4] J.Y. Zhang, D.F. Wang, M.H. Shi. A multiple constrained QoS routing based on firing coupled neural networks. Journal of China Institute of Communications, Vol. 23(7) (2002) pp.40-46.

[5] Q. Hong, Y. Zhang. A new algorithm for finding the shortest paths using PCNNs. Chaos Solitons & Fractals, Vol. 33 (2007) pp.1220-1229.

DOI: https://doi.org/10.1016/j.chaos.2006.01.097

[6] D.M. Zhou, R.C. Nie, D.F. Zhao. Analysis of autowave characteristics for competitive pulse coupled neural network and its application. Neurocomputing, Vol. 72 (2009) p.2331–2336.

DOI: https://doi.org/10.1016/j.neucom.2008.12.008

[7] R.C. Nie, D.M. Zhou, D.F. Zhao et al. CPCNN and its application to multiple constrained QoS route. Journal on Communications, Vol. 31(1) (2010) pp.65-72. (in Chinese).