Although a significant amount of research has investigated the benefits of distributed CEP in terms of scalability and extensibility, there is an ongoing reluctance in deploying distributed CEP in an industrial context. In this paper we present the DHEP system developed together with the IBM R 1 laboratory in Böblingen. It addresses some of the key problems in increasing the acceptance of distributed CEP, for example supporting interoperability between heterogeneous event processing systems. We present the concepts behind the DHEP system and show how those concepts help to achieve scalable and extensible event processing in an industrial context. Moreover, we verify in an evaluation study that the additional cost imposed by the DHEP system is moderate and 'affordable' for the benefits provided.
Complex event processing (CEP) is an emerging software technology for detecting business-relevant situations in streams of events and for providing these detected situations to business processes that are interested in it. While currently CEP-systems are mostly deployed within a single business domain at a limited scale, the cooperative nature of business applications gives reason that complex event processing will soon address multiple business domains and involve an increasingly large number of business events. In order to ensure interoperability as well as efficient utilization of processing and network capability, we motivate the need for heterogeneous correlation technology in the context of business applications. In this article we give an overview of the project “Distributed heterogeneous event processing” (DHEP) involving the IBM Böblingen lab and the Universität Stuttgart, where this need is adressed. The key aspect of the project is the deployment of collections of event correlation rules to a network of heterogeneous event correlation engines. We give an overview of challenges and possible solutions for the dynamic configuration of such environments and present our architecture which supports network-wide cooperation between different correlation engines.
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