Summary

Proceedings of the 2012 International Symposium on Nonlinear Theory and its Applications

2012

Session Number:C1L-A

Session:

Number:539

Traffic Dynamics on Effective Routing Strategy for Complex Networks

Takayuki Kimura,  Tohru Ikeguchi,  

pp.539-542

Publication Date:

Online ISSN:2188-5079

DOI:10.15248/proc.1.539

PDF download (355.5KB)

To establish reliable communication between end users, alleviation of the congestion of packets in the communication networks is the most important problem. As one of the effective routing methods for reliable communication, we have proposed a routing method with chaotic neurodynamics, and another routing method with memory information. For recent works on the routing packets, a packet generating rate is used to evaluate the routing method for the communication networks. Thus, we evaluate the effectiveness of the routing method with the memory information using the packet generating rate in this paper. By using memory information effectively, packets are spread into the communication networks, achieving a higher performance than the conventional routing method for the complex network topology.

[1] M. -B. Hu, W. -X. Wang, R. Jiang, Q. -S. Wu and Y. -H. Wu, “Phase transition and hysteresis in scale-free network traffic,” PRE, vol.75, 036102, 2007.

[2] G. Yan, T. Zhou, B. Hu, Z. -Q. Fu and B. -H. Wang, “Efficient routing on complex networks,” PRE, vol.73, 046108, 2006.

[3] T. Kimura, H. Nakajima and T. Ikeguchi, “A packet routing method for complex networks by a stochastic neural network,” Physica A, vol.376, pp.658-672, 2007,

[4] T. Kimura and T. Ikeguchi, “A new algorithm for packet routing problems using chaotic neurodynamics and its surrogate analysis,” Neural Computation and Applications, vol.16, pp.519-526, 2007.

[5] T. Kimura and T. Ikeguchi, “An optimum strategy for dynamic and stochastic packet routing problems by chaotic neurodynamics,” Integrated Computer-Aided Engineering, vol.14, pp.307-322, 2007.

[6] T. Kimura, T. Hiraguri and T. Ikeguchi, “An Effective Routing Algorithm with Chaotic Neurodynamics for Optimizing Communication Networks,” to appear in the American Journal of Operations Research, 2012.

[7] K. Aihara, T. Tanabe and M. Toyoda, “Chaotic neural network,” Physics Letters A, vol.144, pp.333-340, 1990.

[8] D. J. Watts and S. H. Strogatz, “Collective dynamics of small-world networks,” Nature, vol.393, pp.440-442, 1998.

[9] A. -L. Barabási and R. Albert, “Emergence of scaling in random networks,” Science, vol.286, pp.509-512, 1999.

[10] T. Kimura, T. Ikeguchi and Chi K. Tse, “Efficient Routing Strategy with Memory Information for Complex Networks,” American Journal of Operations Research, Vol.2, pp.73-81, 2012.

[11] P. Echenique, J. Gomez-Gardens and Y. Moreno, “Improved routing strategies for internet traffic delivery,” PRE, vol.70, 056105, 2004.

[12] P. Echenique, J. Gomez-Gardens and Y. Moreno, “Dynamics of jamming transitions in complex networks,” Europhygics Letters, vol.71, pp.325-331, 2005.