Big continuous data: dealing with velocity by composing event streams

However, ex- isting RSP engines do not investigate the trade-off between the reasoning expressiveness and the performance typical of information flow process- ing (IFP) systems:

As we have mentioned, we are interested in detecting events, which are emitted when a function, computed over the data of different distributed nodes, has crossed a specific

We also propose the design of new query language that enables parallel and distributed pattern matching, and stream reasoning by employing query rewriting.. The event data

 DiCEPE (Distributed Complex Event Processing) is a platform that focuses on the integration of CEP engines in distributed systems, and which is capable of using

We extend current event models to incorporate more aspects of (complex) event processing and demon- strate how streams of structured and heterogeneous event objects, represented

The reference framework for process mining focuses on: (i) conceptual models describing processes, organizational structures, and the corresponding relevant data; and (ii) the

Nevertheless, this document raises a number of problems that need to be solved in the process of creating information technology for the synthesis of event- pattern detectors on

Section 4 details the conceptual architecture and how it links CEP modules of events collections, purifications and enrichments as defined by Gal and Hadar (2010) with big data