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Lookup NU author(s): Yinhao Li, Awa Alqahtani, Dr Ellis SolaimanORCiD, Professor Graham MorganORCiD, Professor Raj Ranjan
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
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.
Author(s): Li Y, Alqahtani A, Solaiman E, Perera C, Jayaraman P, Buyya R, Morgan G, Ranjan R
Publication type: Article
Publication status: Published
Journal: Journal of Parallel and Distributed Computing
Year: 2019
Volume: 131
Pages: 161-172
Print publication date: 01/09/2019
Online publication date: 07/05/2019
Acceptance date: 17/04/2019
Date deposited: 13/05/2019
ISSN (print): 0743-7315
ISSN (electronic): 1096-0848
Publisher: Elsevier
URL: https://doi.org/10.1016/j.jpdc.2019.04.016
DOI: 10.1016/j.jpdc.2019.04.016
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