在铁路线路工程平面控制网卫星定位测量中,需要将大量GNSS接收机原始观测数据转换为与接收机无关的RINEX格式文件,以天宝GNSS接收机观测数据为研究对象,采用C#语言对该公司提供的GNSS接收机原始观测数据解码程序Convert To RINEX进行二...在铁路线路工程平面控制网卫星定位测量中,需要将大量GNSS接收机原始观测数据转换为与接收机无关的RINEX格式文件,以天宝GNSS接收机观测数据为研究对象,采用C#语言对该公司提供的GNSS接收机原始观测数据解码程序Convert To RINEX进行二次开发,分析该程序的批处理文件语法规则,然后基于批处理文件调用Convert To RINEX程序的方式,编制天宝GNSS观测数据批处理程序。工程实践表明,该批处理器软件能够方便快捷地将海量原始数据批量转换为RINEX格式文件,极大地节约卫星定位测量数据处理工程中数据预处理所需时间,显著提高了生产效率。展开更多
The evolution of telecommunications has allowed the development of broadband services based mainly on fiber optic backbone networks. The operation and maintenance of these optical networks is made possible by using su...The evolution of telecommunications has allowed the development of broadband services based mainly on fiber optic backbone networks. The operation and maintenance of these optical networks is made possible by using supervision platforms that generate alarms that can be archived in the form of log files. But analyzing the alarms in the log files is a laborious and difficult task for the engineers who need a degree of expertise. Identifying failures and their root cause can be time consuming and impact the quality of service, network availability and service level agreements signed between the operator and its customers. Therefore, it is more than important to study the different possibilities of alarms classification and to use machine learning algorithms for alarms correlation in order to quickly determine the root causes of problems faster. We conducted a research case study on one of the operators in Cameroon who held an optical backbone based on SDH and WDM technologies with data collected from 2016-03-28 to “2022-09-01” with 7201 rows and 18. In this paper, we will classify alarms according to different criteria and use 02 unsupervised learning algorithms namely the K-Means algorithm and the DBSCAN to establish correlations between alarms in order to identify root causes of problems and reduce the time to troubleshoot. To achieve this objective, log files were exploited in order to obtain the root causes of the alarms, and then K-Means algorithm and the DBSCAN were used firstly to evaluate their performance and their capability to identify the root cause of alarms in optical network.展开更多
文件共享服务是对等网络中的一个重要应用,数据传输速率逐渐取代响应延迟成为影响用户体验的首要因素.文中研究了对等网络中的副本管理算法,这对于提高对等网络应用的可靠性,降低带宽消耗具有重要的意义.为了在广域网络存储系统中加速...文件共享服务是对等网络中的一个重要应用,数据传输速率逐渐取代响应延迟成为影响用户体验的首要因素.文中研究了对等网络中的副本管理算法,这对于提高对等网络应用的可靠性,降低带宽消耗具有重要的意义.为了在广域网络存储系统中加速文件共享并降低网络带宽消耗,文中提出了PLAR(Popularity and Locality-based Adaptive Replication)算法.PLAR采用了基于位置信息和流行度的复本管理算法,该算法还同时引入了混合式的服务器选择策略以及远程增强策略.PLAR算法在文中的Granary对等广域网存储系统中得到了实现.实验表明,通过PLAR算法下载速率平均能提高60%以上,有效提高了共享速度并减少带宽消耗.展开更多
文摘在铁路线路工程平面控制网卫星定位测量中,需要将大量GNSS接收机原始观测数据转换为与接收机无关的RINEX格式文件,以天宝GNSS接收机观测数据为研究对象,采用C#语言对该公司提供的GNSS接收机原始观测数据解码程序Convert To RINEX进行二次开发,分析该程序的批处理文件语法规则,然后基于批处理文件调用Convert To RINEX程序的方式,编制天宝GNSS观测数据批处理程序。工程实践表明,该批处理器软件能够方便快捷地将海量原始数据批量转换为RINEX格式文件,极大地节约卫星定位测量数据处理工程中数据预处理所需时间,显著提高了生产效率。
文摘The evolution of telecommunications has allowed the development of broadband services based mainly on fiber optic backbone networks. The operation and maintenance of these optical networks is made possible by using supervision platforms that generate alarms that can be archived in the form of log files. But analyzing the alarms in the log files is a laborious and difficult task for the engineers who need a degree of expertise. Identifying failures and their root cause can be time consuming and impact the quality of service, network availability and service level agreements signed between the operator and its customers. Therefore, it is more than important to study the different possibilities of alarms classification and to use machine learning algorithms for alarms correlation in order to quickly determine the root causes of problems faster. We conducted a research case study on one of the operators in Cameroon who held an optical backbone based on SDH and WDM technologies with data collected from 2016-03-28 to “2022-09-01” with 7201 rows and 18. In this paper, we will classify alarms according to different criteria and use 02 unsupervised learning algorithms namely the K-Means algorithm and the DBSCAN to establish correlations between alarms in order to identify root causes of problems and reduce the time to troubleshoot. To achieve this objective, log files were exploited in order to obtain the root causes of the alarms, and then K-Means algorithm and the DBSCAN were used firstly to evaluate their performance and their capability to identify the root cause of alarms in optical network.
文摘文件共享服务是对等网络中的一个重要应用,数据传输速率逐渐取代响应延迟成为影响用户体验的首要因素.文中研究了对等网络中的副本管理算法,这对于提高对等网络应用的可靠性,降低带宽消耗具有重要的意义.为了在广域网络存储系统中加速文件共享并降低网络带宽消耗,文中提出了PLAR(Popularity and Locality-based Adaptive Replication)算法.PLAR采用了基于位置信息和流行度的复本管理算法,该算法还同时引入了混合式的服务器选择策略以及远程增强策略.PLAR算法在文中的Granary对等广域网存储系统中得到了实现.实验表明,通过PLAR算法下载速率平均能提高60%以上,有效提高了共享速度并减少带宽消耗.
