a statistical framework for efficient monitoring of end-to-end network properties
Network service providers and customers are often concerned with aggregate performance measures that span multiple network paths. Unfortunately, forming such network-wide measures can be difficult, due to the issues of scale involved. As a result, it is of interest to explore the feasibility of methods that dramatically reduce the number of paths measured in such situations while maintaining acceptable accuracy.In previous work [4] we have proposed a statistical framework for efficiently addressing this problem. The key to our method lies in the observation and exploitation of the fact that network paths show significant redundancy (sharing of common links).We now make three contributions in [3]: (1) we generalize the framework to make it more immediately applicable to network measurements encountered in practice; (2) we demonstrate that the observed path redundancy upon which our method is based is robust to variation in key network conditions and characteristics, including the presence of link failures; and (3) we show how the framework may be applied to address three practical problems of interest to network providers and customers, using data from an operating network.
networking statistical analysis algorithms