Cerebrus Solutions Limited

George Bolt

John Manslow

A system for identifying extreme behavior in elements of a network comprises a profiler and a collator. The profiler and the collator perform a method of identifying extreme behavior in the network elements. The profiler maintains one or more group profiles of network elements. Each group profile is associated with a plurality of network elements. The profiler accumulates values of a first function of the contents of an input data stream over a first period of time for each group profile. The input data stream includes at least one field containing a network element reference. The accumulated values of each group profile are compared with a corresponding collation threshold. The collator creates a collation instance for each group profile that reaches the collation threshold. Each collation instance creates a plurality of collation profiles. Each collation profile is associated with one or more network elements from the plurality of network elements corresponding to the group profile that caused the creation of the collation instance. The collator instance accumulates values of a second function of the contents of the input data stream for each collation profile over a second period of time. Extreme behavior of network elements is identified from the accumulated values of the collation profiles.

System and method for identifying extreme behavior in elements of a network

A system for detecting change in a data stream comprising a distribution maintenance engine, a difference determining means and an alert generation engine is disclosed. The system detects change in the alert stream by the distribution maintenance engine maintaining a short term distribution that models the data stream and maintaining a long term distribution that models the data stream. The difference determining means determines the difference between the short term distribution and the long term distribution. The alert generation engine applies a statistical measure to the difference and generates an alert if the measure of the difference exceeds a threshold.

Method and system for detecting change in data streams

In one embodiment, a method of configurably profiling data uses system comprising a pre-processor, a profiler, a post-processor and database. The pre-processor receives data and feedback data and performs configurable first calculations thereon to create data relating to profiling features. The profiler summarizes the profiling features data over a length of time by performing configurable second calculations thereon to create summarized data relating to profiled features. The post-processor performs configurable third calculations the profiled features data to create the feedback data and a profiled output data stream for further processing.

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Hampshire, United Kingdom

George Bolt