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.







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Radzi, N.A.M., Din, N.M., Al-Mansoori, M.H., Mustafa, I.S., Sadon, S.K.: Intelligent dynamic bandwidth allocation algorithm in Upstream EPONs. IEEE/OSA J. Opt. Commun. Netw. 2(3), 148–158 (2010)
Choi, S., Park, J.: SLA-aware dynamic bandwidth allocation for QoS in EPONs. IEEE/OSA J. Opt. Commun. Netw. 2(9), 773–781 (2010)
Lam, C.: Passive optical networks: principles and practice. Academic, Burlington, MA (2007)
Razavi, R., Guild, K.: Multi-constraints fuzzy-logic-based scheduling algorithm for passive optical networks. J. Opt. Netw. 8(4), 346–357 (2009)
Kramer, G., Mukherjee, B., Pesavento, G.: Interleaved polling with adaptive cycle time (IPACT): a dynamic bandwidth distribution scheme in an optical access network. Photon. Netw. Commun. 4(1), 89–107 (2002)
Hwang, I.S., Shyu, Z.D., Ke, L.Y., Chang, C.C.: A novel early DBA mechanism with prediction-based fair excessive bandwidth allocation scheme in EPON. Comput. Commun. 31(9), 1814–1823 (2008)
Zheng, J.: Efficient bandwidth allocation algorithm for Ethernet Passive Optical Networks. IEEE Proc. Commun. 153(3), 464–468 (2006)
Choi, S.Y., Lee, S., Lee, T.J., Chung, M.Y., Choo, H.: Double-phase polling algorithm based on partitioned ONU subgroups for high utilization in EPONs. IEEE/OSA J. Opt. Commun. Netw. 1(5), 484–497 (2009)
Sue, C.C., Cheng, H.W.: A fitting report position scheme for the gated IPACT dynamic bandwidth algorithm in EPONs. IEEE/ACM Trans. Netw. 18(2), 624–637 (2010)
McGarry, M., Maier, M., Reisslein, M.: Ethernet PONs: a survey of dynamic bandwidth allocation (DBA) algorithms. IEEE Commun. Mag. 42(8), 8–15 (2004)
Kramer, Glen, Mukherjee, Biswanath, Dixit, Sudhir, Ye, Yinghua, Hirth, Ryan: Supporting differentiated classes of service in Ethernet Passive Optical Networks. J. Opt. Netw. 1(8), 280–298 (2002)
Luo, Y., Ansari, N.: Bandwidth allocation for multiservice access on EPON. IEEE Commun. Mag. 43(2), 16–21 (2005)
Hwang, J., Yoo, M.: QoS-aware class gated DBA algorithm for the EPON system, International conference on advanced technologies for communications, pp 363–366 (2008)
Assi, C.M., Ye, Y., Dixit, S., Ali, M.A.: Dynamic bandwidth allocation for quality-of-service over Ethernet PONs. IEEE J. Sel. Areas Commun. 21(9), 1467–1477 (2003)
Chen, J., Chen, B., Wosinska, L.: Joint bandwidth scheduling to support differentiated services and multiple service providers in 1G and 10G EPONs. IEEE/OSA J. Opt. Commun. Netw. 1(4), 343–351 (2009)
Peng, J.W., Chang, C.J., Tien, P.L.: PRNN/ERLS-based predictive QoS-promoted DBA scheme for upstream transmission in EPON. Photon. Netw. Commun. 20(1), 17–26 (2010)
Nadia, N., Ajith, A.: Genetic systems programming: theory and experiences. Springer, ISBN-10: 3540298495 (2006)
Zuo, J., Tang, C., Li, C., Yuan, C., Chen, A.: Time series prediction based on gene expression programming. In: International Conference on Advances in WebAge. Information Management 5 th, vol. 3129, 1, pp. 55–56 (2002)
Blake, S., Black, D., Carlson, M., Davies, E., Wang, Z., Weiss, W.: An architecture for differentiated services. IETF RFC 2475 (1998)
Koza, J.R.: Genetic programming II: automatic discovery of reusable programs. MIT Press, Cambridge, MA (1994)
Bakhshaii, A., Stull, R.: Deterministic ensemble forecasts using gene-expression programming. Weather Forecast. 24(5), 1431–1451 (2009)
Bai, X., Shami, A.: Modelling self-similar traffic for network simulation. Technical report, NetRep-2005-01 (2005)
ITU-T Recommendation G.114: One-way transmission time, in series G: transmission systems and media, digital systems and networks (2000)
Shami, A., Bai, X., Assi, C., Ghani, N.: Jitter performance in Ethernet Passive Optical Network. J. Lightwave Technol. 43(4), 1745–1753 (2005)
Jain, R., Durresi, A., Babic, G.: Throughput fairness index: an explanation. ATM Forum/99-0045 (1999)
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Lee, JY., Hwang, IS., Liem, A.T. et al. Genetic expression programming: a new approach for QoS traffic prediction in EPONs. Photon Netw Commun 25, 156–165 (2013). https://doi.org/10.1007/s11107-013-0399-x
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DOI: https://doi.org/10.1007/s11107-013-0399-x