Optimal Sampling Strategies for Multiscale Models with Application to Network Traffic Estimation
Ribeiro, Vinay Joseph; Riedi, Rudolf H.; Baraniuk, Richard G.
This paper considers the problem of determining which set of 2<sup><i>p</i></sup> leaf nodes on a binary multiscale tree model of depth N (<i>N</i>><i>p</i>) gives the best linear minimum mean-squared estimator of the tree root. We find that the best-case and worst-case sampling 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.
tree multiscale optimal sampling networks traffic estimation; Signal Processing for Networking; tree multiscale optimal sampling networks traffic estimation