IoT-CANE: A unified knowledge management system for data-centric Internet of Things application systems

摘要

Identifying a suitable configuration of devices, software and infrastructures in the context of user requirements is fundamental to the success of delivering loT applications. As possible configurations could be large in number and not all configurations are valid, a configuration knowledge representation model can provide ready-made configurations based on loT requirements. Combining such a model within the context of a given user-oriented scenario, it is possible to automate the recommendation of solutions for deployment and long-time evolution of loT applications. However, in the context of Cloud/Edge technologies, that may themselves exhibit significant configuration possibilities that are also dynamic in nature, a more unified approach is required. We present loT-CANE (Context Aware recommendatioN systEm) as such a unified approach. loT-CANE embodies a unified conceptual model capturing configuration, constraint and infrastructure features of Cloud/Edge together with loT devices. The success of loT-CANE is evaluated through an end-user case study. (C) 2019 Elsevier Inc. All rights reserved.