Using cloud association rule data mining approach in optical networks

Bin Ma

doi:10.1117/12.742814

19 November 2007 Using cloud association rule data mining approach in optical networks

Bin Ma

Proceedings Volume 6783, Optical Transmission, Switching, and Subsystems V; 67833S (2007) https://doi.org/10.1117/12.742814
Event: Asia-Pacific Optical Communications, 2007, Wuhan, China

Abstract

In the current DWDM network, one of the critical design issues in the utilization of networks is careful planning to minimize burst dropping resulting from resource contention. The provision of suitable planning before metadata are sent is critical to improve the rate of successful transmission. In this paper, we attempt to adopt a novel data mining approaches to determining a suitable routing path in the OBS network. Instead of using label switching techniques in DWDM, we proposed the hybrid OBS routing planning on the basics of Cloud Association Rules Algorithm, thus reduced the transmission collision rate in OBS routing. This paper searches for the optimal routing path from all the possible routing paths using cloud association rule approach with Apriori-gen algorithm based on the PACNet topology. The heuristic rules discovered by Apriori-gen algorithm are stored in the Knowledge Base (KB) as references for determining the most suitable routing path. The Knowledge Base of the routing path are set up by means of optimal path routing with the highest successful rate which is mined from the database of historical routing paths using cloud association rules. The experiment results show that the successful rates of routing paths obtained by the proposed routing planning approach can effectively improve the successful rates of transmission.

Citation Download Citation

Bin Ma "Using cloud association rule data mining approach in optical networks", Proc. SPIE 6783, Optical Transmission, Switching, and Subsystems V, 67833S (19 November 2007); https://doi.org/10.1117/12.742814

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