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Delay analysis of dynamic bandwidth allocation for triple-play-services in EPON

机译:EPON中三网融合业务动态带宽分配的时延分析

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Today, triple play services may be regarded as required services in telecommunication sector. In the access network, Ethernet Passive Optical Network (EPON) is considered as one of the best solutions to provision triple-play-services. In EPON, the Dynamic Bandwidth Allocation (DBA) algorithm plays a key role to meet the Quality-of-Service (QoS) requirements. Therefore, in this paper, we conduct the delay analysis of DBA so that it can provide a better understanding for the network operators when designing and implementing a DBA algorithm. We use machine learning algorithm such as Random Forest, Decision Tree, kNN, and Naives Bayes and R-programming to build a prediction model and find the important factors affecting the packet delay in EPON system. We run extensive simulation scenarios to build appropriate dataset for training set and testing set. We found that the cycle time selection has a significant impact on the EF delay, AF delay and BE grant. We also found that there was a strong relationship between the EF delay and AF GRANT. Lastly, we conduct performance evaluation to justify what we found. Simulation results show that cycle time is indeed has significant effect on system performances.
机译:如今,三网融合服务可能已被视为电信领域的必备服务。在接入网中,以太网无源光网络(EPON)被认为是提供三重播放服务的最佳解决方案之一。在EPON中,动态带宽分配(DBA)算法在满足服务质量(QoS)要求方面起着关键作用。因此,在本文中,我们对DBA进行了时延分析,以便它可以为网络运营商在设计和实现DBA算法时提供更好的理解。我们使用随机森林,决策树,kNN和Naives Bayes等机器学习算法和R编程来构建预测模型,并找出影响EPON系统中数据包延迟的重要因素。我们运行广泛的模拟方案,以为训练集和测试集构建适当的数据集。我们发现,周期时间的选择对EF延迟,AF延迟和BE授予有重大影响。我们还发现,EF延迟和AF GRANT之间存在很强的关系。最后,我们进行绩效评估以证明我们的发现是合理的。仿真结果表明,周期时间确实对系统性能有重大影响。

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