Dynamic Contextual Goal Management in IoT-Based Systems

• Published in: IEEE internet of things journal 2020-10, Vol.7 (10), p.10708-10718
• Main Authors: Narendra, Nanjangud C., Deb, Novarun, Das, Souvick
• Format: Article
• Language: English
• Subjects: Accidents; Context modeling; Data mining; Data modeling; Data models; goal modeling; Internet of Things; internet of Things (IoT); Lattices; Management; Objectives; Smart cities; Specifications
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2020.3013643

One of the crucial research issues in the Internet of Things (IoT) is to capture the exact intent of the user during the specification of system goals. It is often the case that there is a mismatch between what the user asks for and what the user actually needs. Existing works have tried to filter data based on user-specified goals. In this article, we present our framework that tries to align the user's intent with system goal specifications based on the data being used. Dynamic contextual goal management in IoT-based systems becomes necessary when users start to use more (or less) data than that extracted to fulfill their earlier specified goals. This would require an augmentation of the goals vis-a-vis the used data and the context in which the data was used. To that end, we present the concept of a contextual goal lattice , where goals and their associated contexts are managed appropriately. This would make it easy for future users to specify their goals more accurately and extract precisely the data that they need. We also demonstrate the creation and maintenance of such a lattice structure in a realistic use case of the smart city domain via an implementation prototype. We see from our evaluations that such dynamic contextual goal management is nontrivial in nature.