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Algorithms for anomaly detection in IP networks have been developed and a real-time distributed platform for anomaly detection has been implemented. These algorithms automatically and adaptively detect "soft" network faults (performance degradations) in IP networks. These algorithms are implemented as a reliable and fully distributed real-time software platform called NSAD (Network/Service Anomaly Detector). IP NSAD has the following novel features. First, it provides a flexible platform upon which pre-constructed components can be mixed/matched and distributed (to different machines) to form a wide range of application specific and fully distributed anomaly detectors. Second, anomaly detection is performed on raw network observables (e.g., performance data such as MIB2 and RMON1/2 variables) and algebraic functions of the observables (objective functions), making NSAD an objective driven anomaly detection system of wide detection range and high detection sensitivity. Third, controlled testing demonstrates that NSAD is capable of detecting network anomalies reliably in IP networks.

We identify literature that argues the process of creating knowledge‐based system is often imbalanced. In most knowledge‐based systems, development is often technology‐driven instead of requirement‐driven. Therefore, we argue designers must recognize that evaluation is a critical link in the application of requirement‐driven development models because it provides the information that keeps the iterative developmental process on track. In this study we took a closer look at the decision‐making in the design of a complex performance system in a non‐profit organization. The purpose was to gain insights into the roles and functions of evaluation during the process of building a performance support system. This study adopted an exploratory case study as its inquiry method. Findings suggested that effective communication is as important a function to evaluation as is decision‐making, and that the implementation of evaluation seldom follows the textbook guidelines. That is, evaluation practice is a patchwork history of the designers' knowledge and experience. Further, neither complexity nor the informality of the evaluation protocols seems to influence the quality of decision‐making.