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

Lookup NU author(s): Yinhao Li, Awa Alqahtani, Dr Ellis Solaiman, Dr Graham Morgan, Professor Raj Ranjan

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


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.


Publication metadata

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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