Abstract

Smart solutions must be resilient and adapt to the changes in the environment seamlessly. Due to multiple data flows from Sensors to Smart Solutions, the modeling and the enactment of IoT processes (data and control flows as workflows) is a challenging task. In this work, we present IoT data flows as workflows orchestrated by the events raised in the IoT data flow execution and create/update and deploy the workflow instances (at runtime) to support resilient, smart solutions. Data resilience ensures that data remains reliable, available, and accessible, even when adverse events (such as addition/deletion of sensors, context drift, and exceptions) occur. As the execution of the smart solutions mostly depends on the context (such as location, time, and events), there is a dependency between the context for the data generated and the data requirements for the smart solutions. Thus, there is a need for updating the workflows and adding new workflows as execution progresses for the effective processing of (static, dynamic, and evolving) IoT data. In this paper, we present an implementation framework of our approach and demonstrate our approach for different scenarios addressed by a smart traffic advisor.

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