改进的神经网络EPON动态带宽分配方法  

Improved neural network algorithm in EPON Dynamic Bandwidth Allocation

作　　者：江晓明[1] 朱娜[1] 董亮[1] 李杰[1] 

机构地区：[1]江苏大学计算机科学与通信工程学院,江苏镇江212013

出　　处：《计算机工程与应用》2012年第36期112-115,共4页Computer Engineering and Applications

基　　金：国家自然科学基金(No.60702056);江苏大学大学生实践创新训练计划项目(No.2010060)

摘　　要：动态带宽分配(DBA)是EPON的关键技术,根据数据业务流量的突发性调整了ONU授权时隙的顺序,提出了一种改进的轮询算法,构造了微粒群(PSO)优化的神经网络预测模型,提高了轮询周期内ONU新增数据的预测精度,从而保证了带宽分配公平性。仿真结果表明,该算法在优化带宽资源分配、降低平均数据时延方面均优于传统DBA算法。Dynamic Bandwidth Allocation （DBA） is a key technology of EPON. The paper proposes an improved polling algorithm, adjusts the order of ONU authorization time slot according to the data traffic flow burst characteristics, constructs a neural network prediction model in Particle Swarm Optimization （PSO）, enhances the ONU added data prediction precision in the polling cycle, and thus guarantees bandwidth allocation fairness. The simulation proves that the algorithm performs better in the improvement of bandwidth utilization and has a smaller average packet delay compared with traditional DBA.

关 键 词：以太网无源光网络(EPON) 动态带宽分配 公平性 人工神经网络 微粒群 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]