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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Photonic Network Communications Springer Journals

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

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Publisher
Springer US
Copyright
Copyright © 2013 by Springer Science+Business Media New York
Subject
Computer Science; Computer Communication Networks; Electrical Engineering; Characterization and Evaluation of Materials
ISSN
1387-974X
eISSN
1572-8188
D.O.I.
10.1007/s11107-013-0399-x
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

Photonic Network CommunicationsSpringer Journals

Published: Apr 24, 2013

References

  • 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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