Context-Driven and Real-Time Provisioning of Data-Centric IoT Services in the Cloud

Œe convergence of Internet of Œings (IoT) and the Cloud has signi€cantly facilitated the provision and management of services in large-scale applications such as smart cities. With a huge number of IoT services accessible through clouds, it is very important to model and expose cloud-based IoT services in an ecient manner, promising easy and real-time delivery of cloud-based, data-centric IoT services. Œe existing work in this area has adopted a uniform and ƒat view to IoT services and their data, making it dicult to achieve the above goal. In this paper, we propose a so‰ware framework, called CARIoT for real-time provisioning of cloud-based IoT services and their data, driven by their contextual properties. Œe main idea behind the proposed framework is to structure the description of data-centric IoT services and their real-time and historical data in a hierarchical form in accordance with the end-user application’s context model. CARIoT features design choices and so‰ware services to realize this service provisioning model and the supporting data structures for hierarchical IoT data access. Using this approach, end-user applications can access IoT services and subscribe to their real-time and historical data in an ecient manner at di‚erent contextual levels, e.g., from a municipal district to a street in smart city use cases. We leverage a popular cloud-based data storage platform, called Firebase, to implement the CARIoT framework and evaluate its eciency. Œe evaluation results show that CARIoT’s hierarchical structure imposes no additional overhead with less data noti€cation delay as compared to existing ƒat structures.