Comparing Of Traffic Matrix Algorithms Based On Network Tomography

Today's Internet is a massive, distributed network which continues to explode in size as e-commerce and related activities grow. The heterogeneous and largely unregulated structure of the Internet renders tasks such as dynamic routing, optimized service provision, service-level verification, and detection of anomalous/malicious behavior increasingly challenging tasks. The problem is compounded by the fact that one cannot rely on the cooperation of individual servers and routers to aid in the collection of network traffic measurements vital for these tasks. In many ways, network monitoring and inference problems bear a strong resemblance to other"inverse problems"in which key aspects of a system are not directly observable.Traffic matrices (TM) reflect the volume of traffic that flows between all possible pairs of sources and destinations in a network. Estimation techniques based on partial information are used to populate traffic matrices because amassing sufficient data from direct measurements to populate a traffic matrix is typically prohibitively expensive. The term Network Tomography for the TM estimation problem when the partial data comes from repeated measurements of the traffic flowing along directed links of the network. Network tomography is based on end-end measurements in order to gain the information t indirectly in the network.This paper analyzes the current research actuality. Make some research on the existing algorithm about traffic matrix estimation. Based on the actual experiment environment structure .Input network topology structure and link load data, use the algorithm of traffic matrix estimation to compute the traffic matrix ,through different network structure and link data, compare the algorithm ,then give the further research plan .