There continues to be unfading interest in developing parametric max-stable processes for modelling tail dependencies and clustered extremes in time series data.However,this comes with some difficulties mainly due to ...There continues to be unfading interest in developing parametric max-stable processes for modelling tail dependencies and clustered extremes in time series data.However,this comes with some difficulties mainly due to the lack of models that fit data directly without transforming the data and the barriers in estimating a significant number of parameters in the existing models.In thiswork,we study the use of the sparsemaxima ofmovingmaxima(M3)process.After introducing random effects and hidden Fréchet type shocks into the process,we get an extended maxlinear model.The extended model then enables us to model cases of tail dependence or independence depending on parameter values.We present some unique properties including mirroring the dependence structure in real data,dealing with the undesirable signature patterns found in most parametricmax-stable processes,and being directly applicable to real data.ABayesian inference approach is developed for the proposed model,and it is applied to simulated and real data.展开更多
针对在底层网络可能发生单点和单链路故障情况下的服务功能链(service function chain,SFC)映射问题,提出一种区分等级的可生存SFC映射方法,为提供重要服务的关键SFC预先分配备用资源,为提供普通服务的普通SFC快速重映射失效部分,从而...针对在底层网络可能发生单点和单链路故障情况下的服务功能链(service function chain,SFC)映射问题,提出一种区分等级的可生存SFC映射方法,为提供重要服务的关键SFC预先分配备用资源,为提供普通服务的普通SFC快速重映射失效部分,从而兼顾提高SFC可生存能力和降低底层网络资源开销的需求.首先,在考虑最小化SFC服务时延的条件下,分别为关键SFC和普通SFC的可生存映射问题建立混合整数线性规划模型.其次,提出2种启发式的模型求解算法,其中,面向关键SFC的主备服务路径构建算法采用贪心思想交替进行节点和链路映射,以减小SFC服务时延,并在主备服务路径之间建立桥接路径,以提高路径切换速度和降低路径切换过程的丢包率;面向普通SFC的失效服务路径重建算法引入最大流问题求解失效节点的最佳重映射位置,以提高成功恢复的失效普通SFC数目,并利用改进的Dijkstra最短路径算法选择时延低的重映射路径.最后,在不同网络条件下实验验证了启发式算法的性能,并且在模拟网络环境中所提可生存SFC映射方法能保证SFC的成功运行率在59.2%以上.展开更多
文摘There continues to be unfading interest in developing parametric max-stable processes for modelling tail dependencies and clustered extremes in time series data.However,this comes with some difficulties mainly due to the lack of models that fit data directly without transforming the data and the barriers in estimating a significant number of parameters in the existing models.In thiswork,we study the use of the sparsemaxima ofmovingmaxima(M3)process.After introducing random effects and hidden Fréchet type shocks into the process,we get an extended maxlinear model.The extended model then enables us to model cases of tail dependence or independence depending on parameter values.We present some unique properties including mirroring the dependence structure in real data,dealing with the undesirable signature patterns found in most parametricmax-stable processes,and being directly applicable to real data.ABayesian inference approach is developed for the proposed model,and it is applied to simulated and real data.
文摘针对在底层网络可能发生单点和单链路故障情况下的服务功能链(service function chain,SFC)映射问题,提出一种区分等级的可生存SFC映射方法,为提供重要服务的关键SFC预先分配备用资源,为提供普通服务的普通SFC快速重映射失效部分,从而兼顾提高SFC可生存能力和降低底层网络资源开销的需求.首先,在考虑最小化SFC服务时延的条件下,分别为关键SFC和普通SFC的可生存映射问题建立混合整数线性规划模型.其次,提出2种启发式的模型求解算法,其中,面向关键SFC的主备服务路径构建算法采用贪心思想交替进行节点和链路映射,以减小SFC服务时延,并在主备服务路径之间建立桥接路径,以提高路径切换速度和降低路径切换过程的丢包率;面向普通SFC的失效服务路径重建算法引入最大流问题求解失效节点的最佳重映射位置,以提高成功恢复的失效普通SFC数目,并利用改进的Dijkstra最短路径算法选择时延低的重映射路径.最后,在不同网络条件下实验验证了启发式算法的性能,并且在模拟网络环境中所提可生存SFC映射方法能保证SFC的成功运行率在59.2%以上.
