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

Authors :
Charith Perera
Yinhao Li
Graham Morgan
Rajkumar Buyya
Awatif Alqahtani
Prem Prakash Jayaraman
Rajiv Ranjan
Ellis Solaiman
Source :
Journal of Parallel and Distributed Computing. 131:161-172
Publication Year :
2019
Publisher :
Elsevier BV, 2019.

Abstract

Identifying a suitable configuration of devices, software and infrastructures in the context of user requirements is fundamental to the success of delivering IoT 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 IoT 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 IoT 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 IoT-CANE (Context Aware recommendatioN systEm) as such a unified approach. IoT-CANE embodies a unified conceptual model capturing configuration, constraint and infrastructure features of Cloud/Edge together with IoT devices. The success of IoT-CANE is evaluated through an end-user case study.

Details

ISSN :
07437315
Volume :
131
Database :
OpenAIRE
Journal :
Journal of Parallel and Distributed Computing
Accession number :
edsair.doi...........7421b9683e6a4c8ecf430ba238bbfab4
Full Text :
https://doi.org/10.1016/j.jpdc.2019.04.016