Simulation study on the interactivity of failure detection and signaling congestion control in intelligent optical networks

Simulation study on the interactivity of failure detection and signaling congestion control in... The Intelligent Optical Network (ION) has emerged as a promising technology in the development of optical networks. ION has a separate control plane, where real-time processing is a most substantial feature. However, the complicated control and management infrastructure requires multiple protocols to cooperate in the same signaling network, and jitter may impair real-time processing, like fast failure detection. In this article, the interactivity of failure detection and network congestion control will be analyzed and proposed solutions will be evaluated by simulations. The failure detection protocol in the control plane is inherited from IP networks. However, there is a scalability problem in the ION when requiring fast detection time. Congestion in the signaling network may be caused by various events. It could be fatal when interacting with fast failure detection would trigger a positive feedback. Several solutions will be presented and analyzed with respect to fast and scalable failure detection and congestion control. We performed a series of intensive simulations to study the interactivity of failure detection and congestion control on the 32-node USNET. The simulation results show that the proposed Enhanced Hello protocol performs well in both fast detection mode and congestion state, especially with far less false failure alarms. The Retransmission Reduction mechanism, which is designed to alleviate congestion, can avoid message loss in some degree, but gives little improvement in other aspects. Photonic Network Communications Springer Journals

Simulation study on the interactivity of failure detection and signaling congestion control in intelligent optical networks

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Springer US
Copyright © 2007 by Springer Science+Business Media, LLC
Computer Science; Computer Communication Networks; Electrical Engineering; Characterization and Evaluation of Materials
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