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