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Using Bayesian Belief Networks for Burst Detection in Ethernet Passive Optical Networks

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Moradpoor, Naghmeh, Bashar, Abul, Parr, Gerard, McClean, Sally, Scotney, Bryan and Owusu, G (2011) Using Bayesian Belief Networks for Burst Detection in Ethernet Passive Optical Networks. In: International Conference on Wireless and Optical Communications, Zhengzhou, China. IEEE. 5 pp. [Conference contribution]

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Abstract

The Ethernet Passive Optical Networks (EPONs) have been considered as a promising candidate for the next generation wired access networks for quite some time. In EPONs bandwidth requests and bandwidth allocations are critical issues which need to be addressed efficiently in order to guarantee the End-to-End (ETE) Quality of Service (QoS) for diverse classes of services. In this paper, we discuss the application of a statistical prediction technique based on the Bayesian Belief Networks (BBNs) which provides real-time decision support to the EPONs Dynamic Bandwidth Allocation (DBA) function. We show that in situations of burst traffic it helps the DBA to predict additional bandwidth requirements.

Item Type:Conference contribution (Paper)
Keywords:EPON, BBN, DBA
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
ID Code:22014
Deposited By:Dr Cathryn Peoples
Deposited On:08 May 2012 15:59
Last Modified:08 May 2012 15:59

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