In recent years, applications reacting on or predicting a happening of interest have received increasing attention. One example are business applications such as supply chain management, manufacturing, or e-business where information about the condition and location of business events are of central interest. So-called CEP (complex event processing) systems emerged in order to detect situations resulting from events and to notify business processes about them. These systems are mostly deployed in a centralized fashion receiving events from multiple sources. Especially the recent advance in sensor technology that now enables transmission of condition and location information about goods, persons, and materials in real-time makes the number of event sources grow rapidly making a central processing more challenging. The cooperation with other business partners extends an event-processing system to multiple domains, each of it having its own characteristics like used CEP engine or business rules. In this context, a heterogeneous correlation technology is necessary in order to ensure interoperability as well as efficient utilization of network capability. This diploma thesis is part of the Distributed Heterogeneous Event Processing (DHEP) project involving IBM Böblingen lab and the University of Stuttgart. The objective of the project is to develop a novel generic framework that allows for reuse of existing possible heterogeneous correlation technology distributed over multiple nodes. As part of this project, this thesis addresses three key issues: make use of a novel correlation language that enables interoperability, use a couple of different communication mechanisms in order to support different requirements, and address traffic issues with an intelligent routing mechanism based on correlation rules.