rtCESPA (Real-Time Complex Event Stream Processing Architecture)

“Information flows through electronic channels -- telephone, radio, TV, and the Internet -- contained almost 18 exabytes (OR 18x1018 bytes) of new information in 2002, three and a half times more than is recorded in storage media. Ninety eight percent of this total is the information sent and received in telephone calls - including both voice and data on both fixed lines and wireless.“
-  UC Berkeley's School of Information Management and Systems.

Studies show how information growth rates are reaching dramatic levels. Many systems today are faced with the dilemma of needing to manage huge amounts of information faster and more effectively. It is clear that most part of the generated, but not stored, information is not analyzed to determine its importance and the need of storage.
RtCESPA is focused on processing complex data in storage systems' bounds, in order to analyse and take actions before storing processes. Leading edge technologies will be used to support a reliable open Event-Driven Architecture that can match the necessary performance benchmarking.

Certain business activities (Banks, Facility Management Services, Warehouses) are dependant upon massive amounts of data, produced by heterogenic systems in a heterogenic way, in order to carry out rapid analysis for their decision-making tasks. Other areas (Emergency Rescue, Security, Transport) are influenced by unpredictable and arbitrary incidents produced by external entities. Moreover, the additional need of reacting to high rates of streaming events per second is presented as the most critical necessity.

In the above scenarios, sources vary greatly (applications, services, databases, external systems events, sensor signals, etc.), time is the key factor and an event or reaction is expected to be pushed back to upper layers, decision takers or the Environment that generates the events.
Business Intelligence solutions integrate On-line Analytical Processing (OLAP), Data Mining (DM) and multidimensional metadata structures to automatically search for patterns in large volumes of data with acceptable performance benchmarking. However, these efforts still provide delayed analysis. The project wishes to address these issues and create an intelligent reactivity - driven system capable of rapidly intercepting and analyzing a vast amount of complex events and data; pushing events to certain activities (such as Monitors or Deciders) and/or reacting to outside world actions in real time.

The objective is to define an Event-Driven Architecture based on leading-edge technologies (Event Stream Processing - ESP, Complex Event Processing - CEP) to be applied when Real Time Reactivity to both external and internal Complex Events is required. Additionally, Semantic and AI related technologies will be used for support. A set of supporting tools and languages will be proposed and opened to set the basis for further standardization. On the other hand, a clear objective is to provide seamless integration with SOA (Service-Oriented Architecture)-based systems and make it possible to support solid fusion of Business Processes with Complex Events. Possible application in emergencies, facility and financial management have been detected. Application in networks monitoring are also described.

Real-Time, EDA, CEP, ESP, SOA, Artificial Intelligence

Experts with the above-mentioned technologies.
Partners with proven experience in EDA development and deployment.
Industrial and Public Authorities that handle large amount of information, especially those that have real-time response necessities.

All partners:
Contribution to proposal is required.

Technological Partners (R&D Organizations, SME, Industrial)
Be part of the tech-core to define best practices in EDA development.
Provide expertise in Architecture and related Language Definition.
Provide knowledge and work force in Architecture Design and Implementation.
Support specific language compilers and supporting open tools.
Validate reliability of the technology in different areas.

Industrial end-user Partners (Industrial, Public Authorities):
Provide vertical knowledge on the sector for a candidate application.
Provide a real environment to test project’s results.

Technological Partners with deep expertise in proposal mentioned technologies and application sectors (Industrial, SME, Specific R&D Organisations).
End-User Partners to provide specific problem descriptions and validate the results supporting demonstrators (Industrial and Public Authorities).

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