Internet of Things (IoT) has radically transformed the world; currently, every device can be connected to the Internet and provide valuable information for decision-making. In spite of the fast evolution of technologies accompanying the grow of IoT, we are still faced with the challenge of providing a service oriented architecture, which facilitates the inclusion of data coming together from several IoT devices, data delivery among a system's agents, real-time data processing and service provision to users. Furthermore, context-aware data processing and architectures still pose a challenge, in spite of being key requirements in order to get stronger IoT architectures. To face this challenge, we propose a COLLaborative ConText Aware Service Oriented Architecture (COLLECT), which facilitates both the integration of IoT heterogeneous domain context data-through the use of a light message broker-and easy data delivery among several agents and collaborative participants in the system-making use of an enterprise service bus-. In addition, this architecture provides real-time data processing thanks to the use of a complex event processing engine as well as services and intelligent decision-making procedures to users according to the needs of the domain in question. As a result, COLLECT has a great impact on context-aware decentralized and collaborative reasoning for IoT, promoting context-aware intelligent decision making in such scope. Since context-awareness is key for a wide range of recommender and intelligent systems, the presented novel solution improves decision making in a large number of fields where such systems require to promptly process a variety of ubiquitous collaborative and context-aware data.
Keywords:Decision making Complex event processing Model-driven development Graphical modeling editor SOA 2.0 a b s t r a c t Organizations all around the world need to manage huge amounts of data from heterogeneous sources every day in order to conduct decision making processes. This requires them to infer what the value of such data is for the business in question through data analysis as well as acting promptly for critical or relevant situations. Complex Event Processing (CEP) is a technology that helps tackle this issue by detecting event patterns in real time. However, this technology forces domain experts to define these patterns indicating such situations and the appropriate actions to be executed in their information systems, generally based on Service-Oriented Architectures (SOAs). In particular, these users face the incommodity of implementing these patterns manually or by using editors which are not user-friendly enough. To deal with this problem, a model-driven solution for real-time decision making in event-driven SOAs is proposed and conducted in this paper. This approach allows the integration of CEP with this architecture type as well as defining CEP domain and event pattern through a graphical and intuitive editor, which also permits automatic code generation. Moreover, the solution is evaluated and its benefits are discussed. As a result, we can assert this is a novel solution for bringing CEP technology closer to any user, positively impacting on business decision making processes.
Complex Event Processing (CEP) is an emerging technology which allows us to efficiently process and correlate huge amounts of data in order to discover relevant or critical situations of interest (complex events) for a specific domain. This technology requires domain experts to define complex event patterns, where the conditions to be detected are specified by means of event processing languages. However, these experts face the handicap of defining such patterns with editors which are not user-friendly enough. To solve this problem, a model-driven approach for facilitating user-friendly design of complex event patterns is proposed and developed in this paper. Besides, the proposal has been applied to different domains and several event processing languages have been compared. As a result, we can affirm that the presented approach is independent both of the domain where CEP technology has to be applied to and of the concrete event processing language required for defining event patterns.
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