Fitting heavy-tailed HTTP traces with the new stratified EM-algorithm


Sadre, R. and Haverkort, B.R.H.M. (2008) Fitting heavy-tailed HTTP traces with the new stratified EM-algorithm. In: 4th International Telecommunication Networking Workshop on QoS in Multiservice IP Networks (IT-NEWS), 13-15 Feb 2008, Venice, Italy (pp. pp. 254-261).

open access
Abstract:A typical step in the model-based evaluation of communication systems is to fit measured data to analytically tractable distributions. Due to the increased speed of today's networks, even basic measurements, such as logging the requests at a Web server, can quickly generate large data traces with millions of entries. Employing complex fitting algorithms on such traces can take a significant amount of time. In this paper, we focus on the Expectation Maximization-based fitting of heavy-tailed distributed data to hyper-exponential distributions. We present a data aggregation algorithm which accelerates the fitting by several orders of magnitude. The employed aggregation algorithm has been derived from a sampling stratification technique and adapts dynamically to the distribution of the data. We illustrate the performance of the algorithm by applying it to empirical and artificial data traces.
Item Type:Conference or Workshop Item
Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:
Link to this item:
Official URL:
Export this item as:BibTeX
HTML Citation
Reference Manager


Repository Staff Only: item control page

Metis ID: 250951