STREAM RT DATA PROCESSING & ANALYSIS

“Complex-event processing (CEP), sometimes called event stream processing, is a computing technique in which incoming data about what is happening (event data) is processed as it arrives to generate higher-level, more-useful, summary information (complex events). Complex events represent patterns in the data, and may signify threats or opportunities that require a response from the business. One complex event may be the result of calculations performed on a few or on millions of base events (input) from one or more event sources” (source: Gartner).

In PSYMBIOSYS we apply and extend the IBM PROactive Technology ONline (PROTON) CEP tool for intelligence manufacturing.

PROTON is an integrated platform to support the development, deployment, and maintenance of event-driven and complex event processing (CEP) applications. It is composed of an authoring tool for the definition of the event-driven application and of the run-time engine. PROTON includes the following features:

  • Enables fast development of CEP (complex event processing) applications, also known as Event Processing Networks (EPN).

  • Resolves a major problem—the gap that exists between events reported by various channels and the reactive situations that are the cases to which the system should react. These situations are a composition of events or other situations (e.g., "when at least four events of the same type occur"), or content filtering on events (e.g., "only events that relate to IBM stocks"), or both ("when at least four purchases of more than 50,000 shares were performed on IBM stocks in a single week").

  • Enables an application to detect and react to customized situations without having to be aware of the occurrence of the basic events.

  • Supports various types of contexts (and combinations of them): fixed-time context, event-based context, location-based context, and even detected situation-based context. In addition, more than one context may be available and relevant for a specific event-processing agent evaluation at the same time.

  • Offers easy development using web-based user interface, point-and-click editors, list selections, etc. Rules can be written by non-programmer users.

  • Receives events from various external sources entailing different types of incoming and reported (outgoing) events.

  • Offers a comprehensive event-processing operator set, including joining operators, absence operators, and aggregation operators.

  • Includes context-based rules such as “If it is 10 minutes before trade closing time and we have more than 100 transactions to commit” or “If 4 disk failure events have occurred on the same server in the last 20 minutes”.

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