A Framework for Measuring IoT Data Quality Based on Freshness Metrics

Over the last decade, the proliferation of the Internet of Things (IoT) has produced an overwhelming flow of continuous streaming data. A massive amount of IoT data will be generated in the future. Therefore, it is necessary to create more sophisticated frameworks to measure IoT data quality, considering relevant attributes such as the freshness, reliability and trustworthiness of IoT data. Existing data freshness models and frameworks mostly depend on the timestamp. However, the frequency of IoT data (e.g., data generated by sensors which is measured per millisecond or minute) needs to be considered, that is, IoT data can change frequently. We introduce a new model for measuring IoT data freshness. In our model, we define unreliable IoT data and discard them while considering fresh data. We introduce a formal approach to IoT data freshness including the underlying concepts and definitions. Using this formal approach, we propose an algorithm for the numerical calculation of the freshness attributes. We conduct several sets of experiments and demonstrate the feasibility of the proposed framework by quantifying the performance of the freshness measurement algorithm. We also demonstrate the capability of the framework to capture freshly generated IoT data through a software prototype and several case studies. Finally, we provide a roadmap for future research considering other IoT data quality attributes, such as reliability and trustworthiness.