Context-Driven and Real-Time Provisioning of Data-Centric IoT Services in the Cloud
Amir Taherkordi, Frank Eliassen, Michael J. McDonald, Geir Horn · ACM Transactions on Internet Technology · 2018
The convergence of Internet of Things (IoT) and the Cloud has significantly 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 efficient manner, promising easy and real-time delivery of cloud-based, data-centric IoT services. The existing work in this area has adopted a uniform and flat view to IoT services and their data, making it difficult to achieve the above goal. In this article, we propose a software framework, Context-driven And Real-time IoT (CARIoT) for real-time provisioning of cloud-based IoT services and their data, driven by their contextual properties. The 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 software 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 efficient manner at different 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 efficiency. The evaluation results show that CARIoT’s hierarchical structure imposes no additional overhead with less data notification delay as compared to existing flat structures.