Researches On Internet Performance Monitoring Based On Active Measurements

With the advances in the broadband networking technology, the network scale becomes increasingly magnitude and IP network services trend to be diverse and complicated. Besides, more rigorous schemes to operation, administration and maintenance bring the requirement of building network infrastructure with high QoS service, compared with functions that offered simple connections and controls in the past. However, because of the inherited high isomerizationess, complexities and dynamic natures of the Internet, it is more and more difficult for people to comprehend the performance characteristics and behaviors of network.Monitoring network performance can quantify metrics and describe network capabilities directly via collecting raw data directly. It is not only the basic method for acknowledging network correctly, but also the important foundation for network control, management and business fee counting. Moreover, it is also the premise to address challenges facing network. In the thesis, we summarized systematically the state of the art in network performance measurement and the past progresses as well as important achievements in this area. In addition, we point some critical problems of measuring network performance based on active measurement. Besides, we delve into measuring important metrics from network layer to application layer, traffic data sampling methods and the design and implement of large scale network performance monitoring system. The main innovative achievements of this thesis are as following:(1) This thesis proposes an improved bandwidth measurement algorithm with low cost and rapid convergence. PRM (Probe Rate Model) is one of the important methods for measuring available bandwidth. Unfortunately it still exist some problems, e.g. the long convergence time and large probe traffic. In order to solve these problems, WPathload, a modified available bandwidth measurement algorithm based on delay jitter statistical law, was proposed. WPathload replaces the sending rate of periodical traffic by its arrival rate, and updates the upper limit of available bandwidth, resulting in shortening convergence speed and decreasing the measurement cost. The experimental result indicates that the ameliorated algorithm can sense changes of available bandwidth rapidly and strengthen the capacity of tracing bandwidth changes.(2) This thesis comprehensively studies behavior characteristic of packet pair during available bandwidth measurement. Because PGM (Probe Gap Model) technique, a current available bandwidth measurement method, can be significantly affected by some inference factors, including cross traffic, packet pathology and clock precision, the result of available bandwidth may be overrated or underrated. With theoretical analysis and experimental data, the impact of these factors is quantitatively analyzed in this paper, and the relationship between these factors and measurement result accuracy is also discussed. Finally, we draw many valuable conclusions, which can be used for ameliorating the PGM.(3) This thesis presents a new TCP throughput model based on Gilbert four-state packet loss pattern. The existing TCP throughput model, which adapts simple packet loss or Bernoulli packet loss mechanism, has become an important factor of restricting the accuracy of throughput model. In this thesis, Gilbert four-state model is used for describing the packet lost behavior of end-to-end internet path, and constructing a new model for TCP congestion control. The simulative result shows that the new model is capable of more precision in actual network. In addition, because the throughput measurement tool based on the proposed model will not produce large measurement traffic, it exerts no impact on the real network and can be used for long period on-line measurement.(4) A streaming media service performance monitoring method Based on active application simulation is also presented in this thesis. From the perspective of users, we propose several metrics reflecting the performance of streaming media application, and accomplish measurement tool—RealMeasure, which is based on active business stimulation. The simulative experiment is used for analyzing the influence on streaming media performance caused by bandwidth, frame rate, packet loss and delay. And according to the analysis, an approach to warning a streaming media performance is discussed. At last, to arrange the out of order packets and improve the client performance, we come up with a streaming receiver buffer monitoring and management algorithm to quantitatively measure the degree of reordering in sequences of packets. According to the experimental data, our work can accomplish dynamic control of quality and provide basis for optimizing the streaming media business system.(5) This thesis presents an internet traffic data sampling methodology based on aggregated time-serial evolution trend. Current popular sampling algorithms can't provide accurate approximation of real characteristics under the circumstance of network traffic bursting. The paper develops an adaptive network traffic sampling methodology ADSA (Adaptive Sample) based on aggregated time-serial evolution trend. The ADSA algorithm adaptively adjusts the time interval between consecutive samples according to the evolution trend of network traffic which is estimated from the obtained samples. As a result, it is able to approximate the measured traffic more precisely. Compared with existing popular sampling algorithms, ADSA algorithm can acquire real traffic characteristics via few samples. Besides, it can not only adjust the sampling rate adaptively according to traffic changes, but also can reduce the device cost.(6) This thesis develops a Behavior Analysis-oriented IP network monitoring system. To reflect Internet running behavior characteristic roundly, we design and implement a network monitoring system for the analysis of the behavior characteristics. By monitoring and analyzing traffic behavior, end-to-end behavior, routing, and application behavior characteristic, the system can acquire the basic characteristics of network behavior, which are used for constructing and validating math model of network behavior. In addition, this system can combine network monitoring technology with network data analyzing technology, and bring about a research platform for various theoretic analysis on network behavior.