Multi-resolution resource behavior queries using wavelets

Different adaptive applications are interested in the dynamic behavior of a resource over different fine- to coarse-grain time-scales. The resource's sensor runs at some fine-grain resource-appropriate sampling rate, producing a discrete-time resource signal. It can be very inefficient to to answer a coarse-grain application query by directly using the fine-grain resource signal. We address this gap between the sensor and its different client applications with a novel query model that explicitly incorporates time-scale as a parameter. The query model is implemented on top of an inherently multi-scale wavelet-based representation of the signal (which could be communicated over a set of multicast channels). A query uses only the wavelet coefficients necessary for its time-scale (and thus could listen to a subset of the channels), greatly reducing the data that need to be communicated. We present very promising initial results on host load signals, showing the tradeoff between compactness and query error. Finally, we describe some of the other operations that the wavelet representation enables.