Optical Packet Switching over Arbitrary Physical Topologies using the Manhattan Street Network: An Evolutionary Approach

Optical packet switching over arbitrary physical topologies typically mandates complex routing schemes and the use of buffers to resolve the likely contentions. However, the relatively immature nature of optical logic devices and the limitations with optical buffering provide significant incentive to reduce the routing complexity and avoid optical domain contentions. This paper examines how the Manhattan Street Network (MSN) and a particular routing scheme may be used to facilitate optical packet switching over arbitrary physical topologies. A novel approach, genetic algorithms (GA), is applied to the problem of deploying the MSN (near) optimally in arbitrary physical topologies. A problem encoding is proposed and different implementations of GA described. The optimum GA parameters are empirically selected and GA is successfully used to deploy the MSN in physical topologies of up to 100 nodes. Favourable results are obtained. GA are also seen to out-perform other heuristics at deploying the MSN in arbitrary physical topologies for optical packet switching.

[1]  D. Cotter,et al.  A new packet routing strategy for ultra-fast photonic networks , 1998, IEEE GLOBECOM 1998 (Cat. NO. 98CH36250).

[2]  Biswanath Mukherjee,et al.  Some principles for designing a wide-area WDM optical network , 1996, TNET.

[3]  Manning,et al.  Nonlinear Optics for High-Speed Digital Information Processing. , 1999, Science.

[4]  David Harle,et al.  Ultrafast optical packet switching over arbitrary physical topologies using the Manhattan Street Network , 2001, ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240).

[5]  D. Cotter,et al.  Ultra-high-bit-rate networking: from the transcontinental backbone to the desktop , 1997, IEEE Commun. Mag..

[6]  George N. Rouskas,et al.  A Survey of Virtual Topology Design Algorithms for Wavelength Routed Optical Networks , 1999 .

[7]  Darrell Whitley,et al.  A genetic algorithm tutorial , 1994, Statistics and Computing.

[8]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[9]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[10]  Maxemchuk The Manhattan street network , 1985 .

[11]  I. Chlamtac,et al.  Lightnets: Topologies for High-speed Optical Networks , 1993 .

[12]  Biswanath Mukherjee,et al.  Some principles for designing a wide-area optical network , 1994, Proceedings of INFOCOM '94 Conference on Computer Communications.

[13]  D. J. Smith,et al.  A Study of Permutation Crossover Operators on the Traveling Salesman Problem , 1987, ICGA.

[14]  David Beasley,et al.  An overview of genetic algorithms: Part 1 , 1993 .

[15]  David E. Goldberg,et al.  Alleles, loci and the traveling salesman problem , 1985 .