Automated Composition, Analysis and Deployment of IoT Applications

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Abstract

Building IoT applications of added-value from a set of available devices with minimal human intervention is one of the main challenges facing the IoT. This is a difficult task that requires models for specifying objects, in addition to user-friendly and reliable composition techniques which in turn prevent the design of erroneous applications. In this work, we tackle this problem by first describing IoT applications using abstract models obtained from existing models of concrete devices. Then, we propose automated techniques for building compositions of devices using a repository of available devices, and an abstract goal of what the user expects from such compositions. Since the number of possible solutions can be quite high, we use both filtering and ranking techniques to provide the most pertinent solutions to users. The provided solutions satisfy the given goal and may be analysed with respect to properties such as deadlock-freeness or unmatched send messages. Finally, the application can be deployed using existing execution engines.

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APA

Durán, F., Salaün, G., & Krishna, A. (2019). Automated Composition, Analysis and Deployment of IoT Applications. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11771 LNCS, pp. 252–268). Springer. https://doi.org/10.1007/978-3-030-29852-4_21

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