| Summary: | The ever growing Internet of Things (IoT) paradigm aims to put people’s incorporation into the new phase of connectivity and sensor technology. While, IoT has the potential to deliver new value-added services in order to make life easier and healthier for people, there are still several issues to be addressed in order to harness the widespread dissemination and adoption of the IoT paradigm, considering its potential benefits. In this context, considering an IoT ecosystem holistically i.e. end-to-end which includes the proprietary Operational Technology (OT) comprising of software and hardware to monitor, detect and control the equipment through sensors and actuators and the general Information Technology (IT) which comprises of the data center infrastructure catering to the backend needs of IoT such as compute, storage and network, one major challenge is converging OT with IT. Such an OT/IT convergence has the potential to explore many problems that exist in the end-to-end IoT ecosystem. One such problem is related to drawing actionable insights through operational analytics. The data center paradigm which concerns this research is the Software-Defined Data Center (SDDC) which is touted as the preferred data center paradigm for IoT. While most of the research happening on IoT today deals with the data from the IoT applications and sensors, this research focuses on the plethora of the metadata contained in the end-to-end IoT ecosystem. This research demonstrates the modelling of the end-to-end IoT ecosystem using semantic-based approach such as ontology. We arrive at a cohesive unified ontology unifying the OT and the IT constituents of the IoT fabric with SDDC together with rich context aware attributes embedded in the unified ontology, thereby addressing the problem of OT/IT convergence as well as laying the foundation to explore many solutions to problems pertinent in such a converged OT/IT ecosystem.
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