Using Reinforcement Learning to the Priority-Based Routing and Call Admission Control in WDM Networks

Using reinforcement learning (RL), this paper deals with the problem of call admission control (CAC) and routing in differentiating the services of Wavelength Division Multiplexing (WDM) networks to obtain maximized system revenue. The problem is formulated as a finite-state discrete-time dynamic programming problem. Here we adopt the RL method together with a decomposition approach, to solve this problem that is too complex to be solved exactly and demonstrate that it is able to earn significantly higher revenue than the alternatives.

[1]  Asuman E. Ozdaglar,et al.  Routing and wavelength assignment in optical networks , 2003, TNET.

[2]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[3]  Kumar N. Sivarajan,et al.  Design of logical topologies: a linear formulation for wavelength-routed optical networks with no wavelength changers , 2001, TNET.

[4]  Bo Li,et al.  A dynamic RWA algorithm in a wavelength-routed all-optical network with wavelength converters , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[5]  Biswanath Mukherjee,et al.  Dynamic lightpath establishment in wavelength-routed WDM networks , 2001, IEEE Commun. Mag..

[6]  Zbigniew Dziong,et al.  Call admission and routing in multi-service loss networks , 1994, IEEE Trans. Commun..

[7]  W. Marsden.  I and J , 2012 .

[8]  Timothy X. Brown,et al.  Reinforcement Learning for Call Admission Control and Routing under Quality of Service Constraints in Multimedia Networks , 2002, Machine Learning.

[9]  Anton Schwartz,et al.  A Reinforcement Learning Method for Maximizing Undiscounted Rewards , 1993, ICML.

[10]  Alexander Birman,et al.  Routing and wavelength assignment methods in single-hop all-optical networks with blocking , 1995, Proceedings of INFOCOM'95.

[11]  Ioannis Lambadaris,et al.  A call admission control for service differentiation and fairness management in WDM grooming networks , 2005, Opt. Switch. Netw..

[12]  J. Y. Yen,et al.  Finding the K Shortest Loopless Paths in a Network , 2007 .

[13]  Charles A. Brackett,et al.  Dense Wavelength Division Multiplexing Networks: Principles and Applications , 1990, IEEE J. Sel. Areas Commun..

[14]  Chris Watkins,et al.  Learning from delayed rewards , 1989 .

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

[16]  Richard S. Sutton,et al.  Learning to predict by the methods of temporal differences , 1988, Machine Learning.

[17]  Ahmed Mokhtar,et al.  Adaptive wavelength routing in all-optical networks , 1998, TNET.

[18]  John N. Tsitsiklis,et al.  Call admission control and routing in integrated services networks using neuro-dynamic programming , 2000, IEEE Journal on Selected Areas in Communications.