Hierarchy Bayesian model based services awareness of high-speed optical access networks

Hui-feng Bai

Optoelectronics Letters ›› : 114 -118.

PDF
Optoelectronics Letters ›› :114 -118. DOI: 10.1007/s11801-018-7244-5
Article

Hierarchy Bayesian model based services awareness of high-speed optical access networks

Author information +
History +
PDF

Abstract

As the speed of optical access networks soars with ever increasing multiple services, the service-supporting ability of optical access networks suffers greatly from the shortage of service awareness. Aiming to solve this problem, a hierarchy Bayesian model based services awareness mechanism is proposed for high-speed optical access networks. This approach builds a so-called hierarchy Bayesian model, according to the structure of typical optical access networks. Moreover, the proposed scheme is able to conduct simple services awareness operation in each optical network unit (ONU) and to perform complex services awareness from the whole view of system in optical line terminal (OLT). Simulation results show that the proposed scheme is able to achieve better quality of services (QoS), in terms of packet loss rate and time delay.

Cite this article

Download citation ▾
Hui-feng Bai. Hierarchy Bayesian model based services awareness of high-speed optical access networks. Optoelectronics Letters 114-118 DOI:10.1007/s11801-018-7244-5

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

VanD P, ValcarenghiL, ChincoliM. Optical Switching & Networking, 2014, 14: 11

[2]

LiC, GuoW, WangW. Optics Communications, 2016, 370: 43

[3]

ÖzgürC T, AydınM A, ZaimA H. Optical Switching & Networking, 2015, 15: 29

[4]

HoutsmaV, VeenD V, HarsteadE. Recent Progress on 25G EPON and Beyond, Proceedings of European Conference on Optical Communication, 2016,

[5]

TsutsumiT, SakamotoT, SakaiY. Journal of Lightwave Technology, 2015, 33: 1660

[6]

RoyR, KramerG, HajduczeniaM. IEEE Communications Magazine, 2011, 49: 78

[7]

GarfiasP, GutiérrezL, SallentS. IEEE/OSA Journal of Optical Communications & Networking, 2012, 4: 978

[8]

KhaterN A, OverillR E. Network Traffic Classification Techniques and Challenges, IEEE Tenth International Conference on Digital Information Management, 2016, 3

[9]

HeL, XuC, LuoY. vTC: Machine Learning Based Traffic Classification as a Virtual Network Function, ACM International Workshop on Security in Software Defined Networks & Network Function Virtualization, 2016, 53

[10]

LuC N, HuangC Y, LinY D. Journal of Network & Computer Applications, 2016, 76: 60

[11]

TongaonkarA, TorresR, IliofotouM. Computer Communications, 2015, 56: 35

[12]

BAIH-F, LIM-W, WANGD-S. Acta Photonica Sinica, 2013, 42: 668

[13]

VanD P, ValcarenghiL, DiasM P I. Optics Express, 2015, 23: A1

[14]

JunJ H, YuZ, JungM S. Inter-ONU Scheduling Scheme for QoS Guarantee in 10G EPON, Proceedings of International Conference on Broadband and Wireless Computing, 2010, Fukuoka, Japan, Communication and Applications, 137

[15]

ParkK S, YuZ B, ChoJ H. An Intra-ONU Scheduling Method in 10G EPON Supporting IEEE 802.1 AVB, Proceedings of the Fourth International Conference on Complex, 2010, Krakow, Poland, Intelligent and Software Intensive Systems, 631

PDF

91

Accesses

0

Citation

Detail

Sections
Recommended

/