Research And Implementation Of Performance Monitoring And Traffic Predicting On Telecom Data Network

In this article, the theory and implementation of performance monitoring on telecom data network are systemically studied and analyzed, including network traffic, utilization, availability and end-to-end performance monitoring. To kinds of performance parameters, the scheme and approach of its implementation are presented in detail. A novel method of performance data collecting and storing are also presented. The software design and architecture of one performance monitoring system are described, which is one main parts of the project -Integrated Data Network Management System on NanChang Telecom. On the other hand, the pilot study of model-based network traffic prediction is carried out. The traffic models about autoregressive are analyzed. The ARMA-based network traffic prediction is described and the error of the method is showed, and our experiments in that are presented and analyzed. The application of traffic prediction in network management system is also discussed, and one design framework is given. Performance monitoring is one of the most important parts of network management. By monitoring performance, we get the main values of network parameters, and alerts can be sent to inform system administrator when the values excess aforehand threshold. In terms of performance data, the work state of network can be understood, and its behavior regulations can be found out. It also gives means to plan network, check out and resolve network faults. Traffic monitoring is a fundamental function of network performance monitoring, and the network load can be reflected by monitoring the kinds of traffic information. Resource load can be showed and potential choke point can be found by monitoring the utilization of network devices. It is well known, resources will be wasted in devices with very low utilization, and system performance may decline with very high utilization. By monitoring availability of network element, stability and dependability of network can be denoted. The end-to-end performance, which is the communication performance between a device and one another, including time delay, rate of lost packets and so on, can present the quality of network service. To the all performance parameters mentioned above, the methods of implementations are given in this paper. As is shown in our practical application, the technologies of implementation are of great practical significance, and it provides a good tool for administrator to maintain and administer the network. Our research and implementation are also representative, and the outcomes can be used in telecom data network management in the large majority. In traditional network management, the potential problems will be resolved after receiving the alerts, and it is very possible for the network to have been affected before being settled. This method is called as "response mode". Such as traffic monitoring, the network often are affected badly when alerts are sent out because of excess of traffic threshold, and it is usually no time to avoid it. The model-based network traffic prediction, in which the traffic model is founded on the old data and the trend of traffic in future is displayed, can meliorate the phenomenon. The possibility of exceeding the threshold will be known through the results of prediction, and the alerts will be sent out if it is large enough. Traffic models are used in predicting the network performance and estimating the control scheme of access. The statistic characteristic of practical traffic can be captured in an accurate traffic model. Because there are strong complexity and isomerism in Internet and behavior of network is high paroxysmal and successional, the Markov-Model and Poisson-Model do not adapt to describe and predict the network traffic. As is shown in a mass of researches, the practical network traffic has self-similarity in statistical sense. Intuitively, a process is self-similar if its statistical behavior is independent of the time-scale. The autoregressive models are analyzed in this paper, including AR, ARMA, ARIMA, F-ARIMA and GARMA. The ARMA-based network traffic prediction is described, and it is shown by the following steps: data collecting, data series smoothing, model establishing, predicting and error analyzing. Our experiments are presented and analyzed based on the practical traffic data. As is shown, the method of prediction can work well. In telecom data network, the network management becomes more and more difficult than before because of the increasing scale and complexity and the expanding application business. The integrated data network management system (IDNMS) is attached importance to apply in the realm of telecom. IDNMS's management objects involve a large quantity of devices which are notablely different each other. The system functions include network configurations, network performance, network faults, and even some relational application business. The performance monitoring in IDNMS must deal with and store a great lot of data because of a good many monitored devices, and it need provide a friendly and rapid interface to users. In this article, the software design and system implementation of performance monitoring in our project are presented in detail, including system functions, system architecture, system deployment and design of modules. The appraisement of the system is also shown. In application practice, the system's management objects involving router and switch mainly come from Cisco, Huawei, Ericsson, ZTE, Siemens, and GangWan. As is shown, the system can be used to manage the network efficiently and conveniently. It gives good evidence to the feasibility and validity of our research and design scheme. In the field of network management, much research and system development have been done by many organizations and companies, and...