Abstract: A system, method, and computer program product for benchmarking a stream processing system are disclosed. The method comprises generating a plurality of correlated test streams. A semantically related data set is embedded within each of the test streams in the plurality of correlated test streams. The plurality of correlated test streams is provided to at least one stream processing system. A summary is generated for each of the semantically related embedded data sets. A common identifier, which is transparent to the system being tested, is embedded within each stream in the plurality of correlated test streams. The common identifier is extracted from the output data set generated by the stream processing system. At least one of the stored copies of the summaries and the common identifier are compared to an output data set including a set of zero or more correlation results generated by the stream processing system.

Abstract: An automatic planning system is provided for stream processing workflow composition. End users provide requests to the automatic planning system. The requests are goal-based problems to be solved by the automatic planning system, which then generates plan graphs to form stream processing applications. A scheduler deploys and schedules the stream processing applications for execution within an operating environment. The operating environment then returns the results to the end users.

Abstract: A system and method are described for constructing and implementing generic software agents for automated tuning of computer systems and applications. The framework defines the modules and interfaces to allow agents to be created in a modular fashion. The specifics of the target system are captured by adaptors that provide a uniform interface to the target system. Data in the agent is managed by a metric manager, and controller modules implement the desired control algorithms. The modular structure and common interfaces allow for the construction of generic agents that are applicable to a wide variety of target systems, and can use a wide variety of control algorithms.

Abstract: Disclosed is a controller that includes a curve matching mechanism. The curve matching mechanism employs Fuzzy Logic to compare input curves to standard curves and to thereby characterize the input curves. Also disclosed in an automotive environment for the curve matching mechanism in which a Fuzzy Controller is used to receive time series data (i.e., input curves) and to present the input curves to the curve matching mechanism. The controller then uses the output of the curve matching mechanism to adjust engine function.

Abstract: An improved method for customization of rule-based applications, such as business process rules and policy. A template keyword modifier is used in the source language and an object-oriented framework is used for managing the creation and maintenance of rulesets and individual rules generated through customization of templates. A method provides generation of rulesets and rules and constrained editing of rule logic through use of template variables, template rules and template rulesets. Embodiments allow separation of complex business logic from less complex domain knowledge that can be maintained by a non-programmer domain expert, such as a business manager.

Abstract: A method and structure for a set of rules processed by combining a procedural rule engine and a pattern matching inference engine to compute and apply discounts to customer orders in an electronic commerce system. The rule processing occurs in multiple phases. First all applicable discounts are computed. Then all allowable subsets of discounts are computed. Finally, a set of discounts is selected, based on business policies, and the discounts are applied to the order line items.

Abstract: A method and apparatus for determining the status of a computer system and software applications running on that system and displaying the status to a system administrator are provided. With the apparatus and method, metrics related to a particular application or subsystem are identified and then collected over a predetermined period of time using a data monitoring or collection facility to generate metric history data. Once collected, the metric history data is analyzed by computing a set of parameters representing statistical measures of the metric history data. A set of fuzzy rules are used to define the relationships between metrics and the ultimate application or subsystem status. This metric history analysis phase may be performed periodically such that the fuzzy sets are dynamically redefined at periodic intervals. The fuzzy rules are then evaluated using a fuzzy reasoning process and an overall status indication is generated.