首页> 外文期刊>Statistical modeling: applications in contemporary issues >Estimation of traffic matrices in the presence of long memory traffic
【24h】

Estimation of traffic matrices in the presence of long memory traffic

机译:存在长内存流量时的流量矩阵估计

获取原文
获取原文并翻译 | 示例
           

摘要

The estimation of traffic matrices in a communications network on the basis of a set of traffic measurements on the network links is a well-known problem, for which a number of solutions have been proposed when the traffic does not show dependence over time, as in the case of the Poisson process. However, extensive measurements campaigns conducted on IP networks have shown that the traffic exhibits long range dependence. Here a method is proposed for the estimation of traffic matrices in the case of long range dependence, and its theoretical properties are studied. Its merits are then evaluated via a simulation study. Finally, an application to real data is provided.
机译:基于网络链路上的一组通信量测量来估计通信网络中的通信量矩阵是一个众所周知的问题,当通信量不随时间变化时,已经提出了许多解决方案,例如泊松过程的情况。但是,在IP网络上进行的大量测量活动表明,流量表现出长期的依赖性。提出了一种在距离依赖较大的情况下估计交通矩阵的方法,并对其理论性质进行了研究。然后通过模拟研究评估其优劣。最后,提供了对真实数据的应用程序。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号