HYRA: An Efficient Hybrid Reporting Method for XG-PON Upstream Resource Allocation

Panagiotis Sarigiannidis, Georgios Papadimitriou, Petros Nicopolitidis, Emmanouel Varvarigos, Konstantinos Yiannopoulos

2014

Abstract

The dynamic bandwidth allocation (DBA) process in the modern passive optical networks (PONs) is crucial since it greatly influences the whole network performance. Recently, the latest new generation PON (NGPON) standard, known as 10-gigabit-capable passive optical network (XG-PON), standardized by the international telecommunication union telecommunication standardization sector (ITU-T), emerges as one of the most efficient access networking framework to cope with the demanding needs of the fiber to the x (FTTX) paradigm, where x stands for home (FTTH), bulding (FTTB), or curve (FTTC). Motivated by the fact that the ITU-T specifications leave the bandwidth allocation process open for development by both industry and academia, we propose a novel DBA scheme for effectively delivering data in the upstream direction. Our idea is based on a subtle suggestion induced by the XG-PON specifications; each developed DBA method should combine both status reporting (SR) and traffic monitoring (TM) techniques. This means that a XGPON framework should be cognitive enough in order to be able either to request bandwidth reporting from the connected users or estimate users’ bandwidth demands or both. In this article we cover this gap by proposing a robust learning from experience method by utilizing a powerful yet simple tool, the learning automata (LAs). By combining SR and TM methods, the proposed hybrid scheme, called hybrid reporting allocation (HYRA), is capable of taking efficient decisions on deciding when SR or TM method should be employed so as to maximize the efficacy of the bandwidth allocation process. Simulation results reveal the superiority of our scheme in terms of average packet delay offering up to 33% improvement.

References

  1. Bozicevic, G., Sarjanovic, E., and Tkalic, M. (2004). Distributed internet applications using learning automata. In Electrotechnical Conference, 2004. MELECON 2004. Proceedings of the 12th IEEE Mediterranean, volume 2, pages 599-602 Vol.2.
  2. Economides, A. and Silvester, J. (1988). Optimal routing in a network with unreliable links. In Computer Networking Symposium, 1988., Proceedings of the, pages 288-297.
  3. Effenberger, F. (2010). Tutorial: Xg-pon. In Optical Fiber Communication (OFC), collocated National Fiber Optic Engineers Conference, 2010 Conference on (OFC/NFOEC), pages 1-37.
  4. Eraghi, A. E., Torkestani, J. A., Meybodi, M. R., and Navid, A. H. F. (2011). Cellular learning automata-based channel assignment algorithms for wireless mobile ad hoc networks. In Int Conf Mach Learn Comput IPCSIT, volume 3, pages 173-177.
  5. Han, M.-S. (2014). Dynamic bandwidth allocation with high utilization for xg-pon. In Advanced Communication Technology (ICACT), 2014 16th International Conference on, pages 994-997.
  6. Huang, J. (2008). Robotics, signal processing, decision making and self-reproducing machine learning. In Granular Computing, 2008. GrC 2008. IEEE International Conference on, pages 306-311.
  7. Jain, S., Effenberger, F., Szabo, A., Feng, Z., Forcucci, A., Guo, W., Luo, Y., Mapes, R., Zhang, Y., and O'Byrne, V. (2011). World's first xg-pon field trial. Lightwave Technology, Journal of, 29(4):524-528.
  8. Joshi, T., Ahuja, D., Singh, D., and Agrawal, D. (2008). Sara: Stochastic automata rate adaptation for ieee 802.11 networks. Parallel and Distributed Systems, IEEE Transactions on, 19(11):1579-1590.
  9. Kanonakis, K. and Tomkos, I. (2009). Offset-based scheduling with flexible intervals for evolving gpon networks. Lightwave Technology, Journal of, 27(15):3259-3268.
  10. Kumar, N., Iqbal, R., James, A., and Dua, A. (2013). Learning automata based contention aware data forwarding scheme for safety applications in vehicular ad hoc networks. In e-Business Engineering (ICEBE), 2013 IEEE 10th International Conference on, pages 385- 392.
  11. Lee, Y., Lee, D., Yoo, H., and Kim, Y. (2013). Fast management of onus based on broadcast control channel for a 10-gigabit-capable passive optical network (xg-pon) system. Communications and Networks, Journal of, 15(5):538-542.
  12. Misra, S., Krishna, P., Saritha, V., and Obaidat, M. (2013). Learning automata as a utility for power management in smart grids. Communications Magazine, IEEE, 51(1):98-104.
  13. Mullerova, J., Korcek, D., and Dado, M. (2012). On wavelength blocking for xg-pon coexistence with gpon and wdm-pon networks. In Transparent Optical Networks (ICTON), 2012 14th International Conference on, pages 1-4.
  14. Navid, A. (2010). Selarp: Scalable and energy-aware learning automata-based routing protocols for wireless sensor networks. In Sensor Technologies and Applications (SENSORCOMM), 2010 Fourth International Conference on, pages 570-576.
  15. Nicopolitidis, P., Papadimitriou, G. I., Pomportsis, A. S., Sarigiannidis, P., and Obaidat, M. (2011). Adaptive wireless networks using learning automata. Wireless Communications, IEEE, 18(2):75-81.
  16. Sarigiannidis, A., Nicopolitidis, P., Papadimitriou, G., Sarigiannidis, P., and Louta, M. (2011). Using learning automata for adaptively adjusting the downlinkto-uplink ratio in ieee 802.16e wireless networks. In Computers and Communications (ISCC), 2011 IEEE Symposium on, pages 353-358.
  17. Sarigiannidis, P., Louta, M., Balasa, E., and Lagkas, T. (2013a). Adaptive sensing policies for cognitive wireless networks using learning automata. In Computers and Communications (ISCC), 2013 IEEE Symposium on, pages 000470-000475.
  18. Sarigiannidis, P., Papadimitriou, G., Nicopolitidis, P., and Varvarigos, E. (2013b). Ensuring fair downlink allocation in modern access networks: The xg-pon framework. In Communications and Vehicular Technology in the Benelux (SCVT), 2013 IEEE 20th Symposium on, pages 1-5.
  19. Venkata Ramana, B., Manoj, B. S., and Murthy, C. (2005). Learning-tcp: a novel learning automata based reliable transport protocol for ad hoc wireless networks. In Broadband Networks, 2005. BroadNets 2005. 2nd International Conference on, pages 484-493 Vol. 1.
  20. Yoshimoto, N., Kani, J., Kim, S.-Y., Iiyama, N., and Terada, J. (2013). Dsp-based optical access approaches for enhancing ng-pon2 systems. Communications Magazine, IEEE, 51(3):58-64.
Download


Paper Citation


in Harvard Style

Sarigiannidis P., Papadimitriou G., Nicopolitidis P., Varvarigos E. and Yiannopoulos K. (2014). HYRA: An Efficient Hybrid Reporting Method for XG-PON Upstream Resource Allocation . In Proceedings of the 5th International Conference on Optical Communication Systems - Volume 1: OPTICS, (ICETE 2014) ISBN 978-989-758-044-4, pages 5-14. DOI: 10.5220/0005048200050014


in Bibtex Style

@conference{optics14,
author={Panagiotis Sarigiannidis and Georgios Papadimitriou and Petros Nicopolitidis and Emmanouel Varvarigos and Konstantinos Yiannopoulos},
title={HYRA: An Efficient Hybrid Reporting Method for XG-PON Upstream Resource Allocation},
booktitle={Proceedings of the 5th International Conference on Optical Communication Systems - Volume 1: OPTICS, (ICETE 2014)},
year={2014},
pages={5-14},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005048200050014},
isbn={978-989-758-044-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Optical Communication Systems - Volume 1: OPTICS, (ICETE 2014)
TI - HYRA: An Efficient Hybrid Reporting Method for XG-PON Upstream Resource Allocation
SN - 978-989-758-044-4
AU - Sarigiannidis P.
AU - Papadimitriou G.
AU - Nicopolitidis P.
AU - Varvarigos E.
AU - Yiannopoulos K.
PY - 2014
SP - 5
EP - 14
DO - 10.5220/0005048200050014