Context Aware Cohesive Ontology for IoT Deployed With Software Defined Data Centres SDDC

Abstract

newlineAbstract newlineThe ever shifting Internet of Things ( IoT) paradigm aims to put people s incorpora- newlinetion into the new phase of connectivity and sensor technology. IoT has the potential to newlinedeliver new value-added services in order to make life easier and healthier for people, newlineincrease market productivity, and facilitate the growth of smarter, and more sustainable newlinesocieties, ecosystems and nations, in an opportunity to address each individual physical newlineentity and make it a part of a global network. There are still several issues to be addressed newlinein order to harness the widespread dissemination and adoption of the IoT paradigm, con- newlinesidering its potential benefits. In this context, considering an IoT ecosystem holistically newlinei.e. end-to-end which includes the proprietary Operational Technology (OT) compris- newlineing of software and hardware to monitor, detect and control the equipment through newlinesensors and actuators and the general Information Technology (IT) which comprises of newlinethe data center infrastructure catering to the backend needs of IoT such as compute, newlinestorage and network, one major challenge is converging OT with IT. Such an OT/IT newlineconvergence has the potential to explore many problems that exist in the end-to-end newlineIoT ecosystem. While one important problem is related to managing the resources in newlinethe end-to-end IoT ecosystem, another problem is related to drawing actionable insights newlinethrough operational analytics. The data center paradigm which concerns this research is newlinethe Software-Defined Data Center (SDDC) which is touted as the preferred data center newlineparadigm for IoT. While most of the research happening on IoT today deals with the newlinedata from the IoT applications and sensors, this research focuses on the plethora of the newlinemetadata contained in the end-to-end IoT ecosystem. newlineThis thesis demonstrates the modelling of the end-to-end IoT ecosystem using newlinesemantic-based approach such as ontology. We arrive at a cohesive unified ontol- newlineogy which unifies the OT and the IT constituents of the IoT fabric with SDDC together newlinewith rich context aware attributes embedded in the unified ontology, thereby addressing newlinethe problem of OT/IT convergence. Our research problem is broken down into four newlinevectors. newlinev newline The first vector concerns with the building of a platform by constructing an newlineunified ontological model to represent the end-to-end IoT fabric with SDDC. This newlineis accomplished by enhancing the open source OpenIoT/SSN (Semantic Sensor newlineNetwork) ontology from W3C, designing the SDDC ontology and unifying these newlineontologies together with the cloud computing ontology so as to align the concepts newlineof each of these ontologies by using the ontology design principles. newline The next three vectors demonstrate the power of our cohesive context-aware ontol- newlineogy using relevant context-aware attributes for multiple vectors of IoT SDDC/cloud newlinethrough the use cases which make use of the platform to address the challenges in newlinethe end-to-end IoT pertinent to the OT/IT convergence. Specifically, the following newlinechallenges are explored: newline Managing of resources in the end-to-end IoT fabric with SDDC. newline Power Profiling of the end-to-end IoT fabric with SDDC. newline Carrying out predictive failure analyticts in the end-to-end IoT fabric with newlineSDDC using an ontology based digital twin approach. newlineThus, as a part of the research work carried out in this thesis, using semantic newlinebased approach such as ontology, a cohesive context-aware ontology representing the newlineholistic end-to-end IoT ecosystem with SDDC has been designed and, a proof of concept newlineimplemented. The results obtained are very encouraging towards the establishment of a newlinesolution for converging the OT and IT parts of the IoT ecosystem, thereby paving the way newlineto solve many problems pertinent to the end-to-end IoT ecostem using the plethora of metadata newlineavailable.