Maximum likelihood estimation of the flow size distribution tail index from sampled packet data Export

@inproceedings{citeulike:4970486, abstract = {In the context of network traffic analysis, we address the problem of estimating the tail index of flow (or more generally of any group) size distribution from the observation of a sampled population of packets (individuals). We give an exhaustive bibliography of the existing methods and show the relations between them. The main contribution of this work is then to propose a new method to estimate the tail index from sampled data, based on the resolution of the maximum likelihood problem. To assess the performance of our method, we present a full performance evaluation based on numerical simulations, and also on a real traffic trace corresponding to internet traffic recently acquired.}, address = {New York, NY, USA}, author = {Loiseau, Patrick and Gon\c{c}alves, Paulo and Girard, St\'{e}phane and Forbes, Florence and Pascale}, booktitle = {SIGMETRICS '09: Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems}, citeulike-article-id = {4970486}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1555349.1555380}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1555349.1555380}, doi = {10.1145/1555349.1555380}, isbn = {978-1-60558-511-6}, keywords = {heavy-tail}, location = {Seattle, WA, USA}, pages = {263--274}, posted-at = {2009-06-26 10:00:42}, priority = {2}, publisher = {ACM}, title = {Maximum likelihood estimation of the flow size distribution tail index from sampled packet data}, url = {http://dx.doi.org/10.1145/1555349.1555380}, year = {2009} }

TY - CONF ID - citeulike:4970486 L3 - citeulike-article-id:4970486 N2 - In the context of network traffic analysis, we address the problem of estimating the tail index of flow (or more generally of any group) size distribution from the observation of a sampled population of packets (individuals). We give an exhaustive bibliography of the existing methods and show the relations between them. The main contribution of this work is then to propose a new method to estimate the tail index from sampled data, based on the resolution of the maximum likelihood problem. To assess the performance of our method, we present a full performance evaluation based on numerical simulations, and also on a real traffic trace corresponding to internet traffic recently acquired. CY - Seattle, WA, USA SN - 978-1-60558-511-6 AD - New York, NY, USA EP - 274 TI - Maximum likelihood estimation of the flow size distribution tail index from sampled packet data PB - ACM T2 - SIGMETRICS '09: Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems SP - 263 KW - heavy-tail AU - Loiseau, Patrick AU - Gon\c{c}alves, Paulo AU - Girard, St\'{e}phane AU - Forbes, Florence AU - Pascale PY - 2009/// UR - http://dx.doi.org/10.1145/1555349.1555380 ER -