Augmenting context with power information for green context-awareness in smart environments - Mahmud, Umar; Hussain, Shariq (Frontiers in Computer Science, 2024)
The increase in the use of smart devices has led to the realization of the Internet-of-Everything (IoE). At the heart of an IoE environment is a Context-Aware System, that facilitates service discovery, delivery, and adaptation based on context classification. The context has been defined in a domaindependent way, traditionally. The classical models of context have been focused on rich context and lack Cost of Context (CoC) that can be used for decision support. The authors present a philosophyinspired mathematical model of context that includes confidence in activity classification of context, the actions performed, and the power information. Since a single recurring activity can lead to distinct actions performed at different times, it is better to record the actions. The power information includes the power consumed in the complete context processing and is a quality attribute of the context. Power consumption is a useful metric as CoC and is suitable for power-constrained context awareness. To demonstrate the effectiveness of the proposed work, example contexts are described, and the context model is presented mathematically in this paper. The context is aggregated with power information as well as actions and the confidence on the classification outcome leads to the concept of situational context. Results show that the context gathered through sensor data and deduced through remote services can be made more rich with CoC parameters.