Towards data-as-a-service provisioning with high-quality data

Given the large amount of sensed data by IoT devices and various wireless sensor networks, traditional data services lack the necessary resources to store and process that data, as well as to disseminate high-quality data to a variety of potential consumers. In this paper, we propose a framework for Data as a Service (DaaS) provisioning, which relies on deploying DaaS services on the cloud and using a DaaS agency to mediate between data consumers and DaaS services using a publish/subscribe model. Furthermore, we describe a decision algorithm for the selection of appropriate DaaS services that can fulfill consumers’ requests for high-quality data. One of the benefits of the proposed approach is the elasticity of the cloud resources used by DaaS services. Moreover, the selection algorithm allows ranking DaaS services by matching their quality-of-data (QoD) offers against the QoD needs of the data consumer. © Springer Science+Business Media Singapore 2017.