Genetic expression programming: a new approach for QoS traffic prediction in EPONs

Genetic expression programming: a new approach for QoS traffic prediction in EPONs The Ethernet passive optical network is being regarded as the most promising for next-generation optical access solutions in the access networks. In time division multiplexing, passive optical network technology (TDM-PON) and the dynamic bandwidth allocation (DBA) play a crucial key role to achieve efficient bandwidth allocation and fairness among subscribers. Therefore, the traffic prediction in DBA during the waiting time must be put into the account. In this paper, we propose a new prediction approach with an evolutionary algorithm genetic expression programming (GEP) prediction incorporated with Limited IPACT referred as GLI-DBA to tackle the queue variation during waiting times as well as to reduce the high-priority packet delay. Simulation results show that the GEP prediction in DBA can reduce the expedited forwarding (EF) packet delay, shorten the EF queue length, enhance the quality of services and maintain the fairness among the optical network units (ONUs). We conducted and evaluated the detail simulation in two different scenarios with distinctive traffic proportion. Simulation results show that the GLI-DBA has EF packet delay improvement up to 30 % over dynamic bandwidth allocation for multiple of services (DBAM). It also shows that our proposed prediction scheme performs better than the DBAM when the number of ONUs increases. Photonic Network Communications Springer Journals

Genetic expression programming: a new approach for QoS traffic prediction in EPONs

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Springer US
Copyright © 2013 by Springer Science+Business Media New York
Computer Science; Computer Communication Networks; Electrical Engineering; Characterization and Evaluation of Materials
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  • Intelligent dynamic bandwidth allocation algorithm in Upstream EPONs
    Radzi, N.A.M.; Din, N.M.; Al-Mansoori, M.H.; Mustafa, I.S.; Sadon, S.K.

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