Bin Lin, Aaron B. Brown, et al.
ICAC 2006
Service providers typically define quality of service problems using threshold tests, such as `Are HTTP operations greater than 12 per second on server XYZ?' Herein, we estimate the probability of threshold violations for specific times in the future. We model the threshold metric (e.g., HTTP operations per second) at two levels: (1) non-stationary behavior (as is done in workload forecasting for capacity planning) and (2) stationary, time-serial dependencies. Our approach is assessed using simulation experiments and measurements of a production Web server. For both assessments, the probabilities of threshold violations produced by our approach lie well within two standard deviations of the measured fraction of threshold violations.
Bin Lin, Aaron B. Brown, et al.
ICAC 2006
Asit Dan, Dinkar Sitaram, et al.
MM 1994
Joseph L. Hellerstein
LCN 2004
Chang-Shing Perng, Haixun Wang, et al.
ICDM 2001