Abstract: A method and system is described that adaptively adjusts an eService management system by using feedback control. Behavior experts are distributed at different levels of the hierarchy of the eService management system. Within the hierarchy, feed-forward reasoning is performed from lower level behavior experts to the higher level behavior experts. A method for identifying bottlenecks is described and utilized. The performance of these behavior experts is compared with various objective functions. The discrepancies are used to adjust the system.

Abstract: An arrangement is provided for generating early warning of threshold violations in e-service management systems. The behavior of a variable is modeled statistically based on a plurality of data values of a variable collected over a period of time. The modeling generates a behavior model for the variable, represented by a set of model parameters. An early warning for a threshold violation of the variable with respect to a threshold is generated based on the behavior model and a plurality of data values of the variable collected online. The abnormal behavior of the variable is detected or forecasted according to online data values of the variable and the early warning generated.

Abstract: An arrangement is provided for generating early warning of threshold violations in e-service management systems. The behavior of a variable is modeled statistically based on a plurality of data values of a variable collected over a period of time. The modeling generates a behavior model for the variable, represented by a set of model parameters. An early warning for a threshold violation of the variable with respect to a threshold is generated based on the behavior model and a plurality of data values of the variable collected online. The abnormal behavior of the variable is detected or forecasted according to online data values of the variable and the early warning generated.