论文信息 - Case-Based Reasoning (CBR) to estimate the Q-factor in optical networks: An initial approach

Case-Based Reasoning (CBR) to estimate the Q-factor in optical networks: An initial approach

We discuss the potential of Case-Based Reasoning (CBR) to estimate the Q-factor in optical networks. CBR is an artificial intelligence technique which solves new problems based on the solutions of similar past problems. In this paper, as a first step, we consider a very simple scenario and develop a CBR method to estimate the Q-factor in optical links with cascades of amplifiers. While this is a toy problem, the results obtained are promising, as the CBR system performs a successful classification into good quality or low quality of transmission links in 94% of cases.

[1] Cristina Cervello-Pastor,et al. Demonstration of C/S based hardware accelerated QoT estimation tool in dynamic impairment-aware optical network , 2010, 36th European Conference and Exhibition on Optical Communication.

[2] Ioannis Tomkos,et al. A survey on physical layer impairments aware routing and wavelength assignment algorithms in optical networks , 2009, Comput. Networks.

[3] Ian D. Watson,et al. Applying case-based reasoning - techniques for the enterprise systems , 1997 .

[4] Chava Vijaya Saradhi,et al. Physical layer impairment aware routing (PLIAR) in WDM optical networks: issues and challenges , 2009, IEEE Communications Surveys & Tutorials.

[5] Luis Velasco,et al. Experimental Demonstration of an Impairment Aware Network Planning and Operation Tool for Transparent/Translucent Optical Networks , 2011, Journal of Lightwave Technology.

[6] Rubén M. Lorenzo,et al. Joint optimization of delay and congestion in wavelength-routed optical networks using genetic algorithms , 2009, Photonic Network Communications.

[7] Agnar Aamodt,et al. Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..