Context-awareness and demand-driven evaluation in heterogeneous distributed systems

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This research proposal aims at the definition of a theoretically sound framework to introduce the notion of context-aware system interoperability protocol, context-aware middleware, as well as the associated definition and implementation of a programming language semantics based on a demand-driven evaluation method. We propose to integrate our past theoretical and practical results in this framework, which include: (1) a sound theory of context calculus; (2) a demand-driven evaluation semantics, including a language-independent type system necessary for such an implementation; (3) validation of the approach vs scalability and ease of use as to improve existing methodologies in the specific application and middleware domains, e.g. SOA, and cloud, grid, and mobile computing which are increasingly context-aware. Context awareness and its corresponding demand-driven computation model can be applied to the service-oriented architecture (SOA) model of distributed computing, enabling service-oriented clients to gather their own context and make service-oriented server demands based on their own context, and the services to be defined according to the context of the service demands. On another spectrum, new computing models such as grid computing and cloud computing are now generally relying on the notion of context in order to constraint or direct the computational resources being used by processing demands. Again, the notion of context-aware middleware, coupled with a corresponding demand-driven evaluation model fits exactly this current need. We will re-use and expand our previous best theoretical results and their practical component-based realization in the above mentioned domains of SOA, cloud grid, and mobile computing and their applications, to unify the approach, test and validate the scalability and usability of various context-aware paradigms in a uniform research evaluation platform.