OPTIMAL SAMPLING STRATEGIES FOR MULTISCALE MODELS WITH APPLICATION TO NETWORK TRAFFIC ESTIMATION Knay

This paper considers the problem of determining which set of 2P leaf nodes on a binary multiscale tree model of depth N ( N > p ) gives the best linear minimum mean-squared estimator of the tree root. We find that the best-case and worst-case sanipling choices depend on the correlation structure of the tree. This problem arises in Internet traffic estimation. where the goal is to estimate the average traffic rate on a network path based on a limited number of traffic samples.