基于自然连接度的无标度网络断边重连仿真  

A Scale-Free Network Reconnection Simulation Based on Natural Connectivity

在线阅读下载全文

作  者:莫永华[1] MO Yong-hua(Institute of information technology,Guilin University of Electronic Technology,Guilin Guangxi 541004,China)

机构地区:[1]桂林电子科技大学信息科技学院,广西桂林541004

出  处:《计算机仿真》2020年第2期312-316,共5页Computer Simulation

摘  要:针对传统网络断边重连技术不能准确确定无标度网络故障位置,造成断边链路数据重构性能较差的问题,提出基于自然连接度的无标度网络下断边重连技术。将DeviceNet作为核心触发协议、CAN协议作为底层通信协议,构造Dramp流量控制策略;修正逻辑点带宽,捕获自然连接错误帧事件;在无标度网络链路两端建立源观测点,整合错误事件并去除掉观测位置信息,根据时间节点提取多维度源节点数据,完成关联故障定位,最后根据链路重构法及DNS域名解析,以链路负载为核心,重构传输链路完成断边重连。仿真结果表明,所提方法能够准确标定无标度网络故障位置,有效重连无标度断边网络。Traditionally,the network reconnection technology can not accurately determine the fault location of scale-free network,resulting in poor performance of data reconstruction.Therefore,a reconnection method in scale-free networks based on natural connectivity was put forward.Firstly,DeviceNet was used as the core trigger protocol and CAN protocol was taken as the underlying communication protocol,and then Dramp flow control strategy was established.Secondly,the bandwidth of logic point was corrected and the error frame event during the natural connection was captured.Thirdly,the source observation point on both ends of scale-free network link was built,and the error events were integrated to remove the observation position information.Moreover,the multi-dimensional source node data was extracted by the time node,and thus to complete the associated fault location.According to the link reconstruction method and DNS domain name resolution,the link load was taken as the core,so that the transmission link was reconstructed to complete the broken reconnection.Simulation results show that the proposed method can accurately calibrate the fault location of scale-free network and effectively reconnect the scale-free broken network.

关 键 词:自然连接 无标度 断边 观测位置 网络干线 

分 类 号:F272[经济管理—企业管理]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象