Reserarch The Detection Applications Of Network Quality

Along with the rapid development of network technology as well as a significant increase in the number of the network users, network structure is becoming more and more complex, which cause a sharp rise in network data flow, the abnormal flow data is not only a waste of resources,but also reduce the independent utilization of the network, the usability and security of the network is an important premise for the normal use of the network. Traffic data detection is the basis of application for network quality detection, to carry on the corresponding remedial measures for the abnormal flow phenomenon, so the traffic data of detection technology is of great significance for the analysis of network and network management.When the network interface generats a lager traffic, collecting data on the network interface can not be completely captured, and there is the phenomenon of missing data packets, or can not timely analyzing data flow completely for huge data traffic.This will not be able to better analyze network traffic characteristics. This paper proposes a network quality detection system based on piecewise random sampling, segmented sampling method can effectively reduce the amount of data collection work flow, random sampling method can effectively capture network data burst with the use of flow similarity, and reduce the detection system resource requirements and reduce the workload of the flow probe. When the network interface generats a smaller traffic,to probe the network with capturing the fully traffic data.According to the characteristic parameters, analyze traffic data and statics the collected traffic data, the analysis of historical data as the flow reference model. This paper propose a static threshold abnormal flow model based on static partition method, Compared with the traditional traffic model with a global threshold method, this method can be more effective in detecting abnormal flow generation.When the current threshold is higher than the reference model,firstly characterized this event as unusual problem, and collected data traffic characteristics analysis for abnormal malicious traffic and take appropriate remedial measures to reduce the loss of using the network.Finally, tesing the functions for the finished network quality detection system to verify the feasibility of the system, collect data traffic on the network, and analysis and statistics the flow characteristics.