Wayeb: a Tool for Complex Event Forecasting

A Complex Event Processing (CEP) system takes as input a stream of events, along with a set of patterns, defining relations among the input events, and detects instances of pattern satisfaction, thus producing an output stream of complex events . Typically, an event has the structure of a tuple of values which might be numerical or categorical, with the event type and timestamp being the most common attributes. Since time is of critical importance for CEP, a temporal formalism is used in order to define the patterns to be detected. Such a pattern imposes temporal (and possibly atemporal) constraints on the input events, which, if satisfied, lead to the detection of a complex event. Efficient processing is of paramount importance since complex events must be detected with very strict latency requirements.