Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/38618
Title: The Effects of Relative Importance of User Constraints in Cloud of Things Resource Discovery: A Case Study
Authors: Nunes, Luiz H.
Estrella, Júlio C.
Delbem, Alexandre N.
Perera, Charith
Reiff-Marganiec, Stephan
First Published: Dec-2016
Presented at: International Workshop on Clouds and (eScience) Applications Management (Cloud AM 2016) Tongji University - Shanghai, China.
Start Date: 7-Dec-2016
End Date: 7-Dec-2016
Publisher: Association for Computing Machinery
Citation: Computers and Electrical Engineering - International Workshop on Clouds and (eScience) Applications Management (Cloud AM 2016)
Abstract: Over the last few years, the number of smart objects connected to the Internet has grown exponentially in comparison to the number of services and applications. The integration between Cloud Computing and Internet of Things, named as Cloud of Things, plays a key role in managing the connected things, their data and services. One of the main challenges in Cloud of Things is the resource discovery of the smart objects and their reuse in different contexts. Most of the existent work uses some kind of multi-criteria decision analysis algorithm to perform the resource discovery, but do not evaluate the impact that the user constraints has in the final solution. In this paper, we analyse the behaviour of the SAW, TOPSIS and VIKOR multi-objective decision analyses algorithms and the impact of user constraints on them. We evaluated the quality of the proposed solutions using the Pareto-optimality concept.
DOI Link: 10.1145/2996890.3007867
ISSN: 0045-7906
ISBN: 978-1-4503-4616-0
eISSN: 1879-0755
Links: http://dl.acm.org/citation.cfm?id=3007867
http://hdl.handle.net/2381/38618
Version: Post-print
Status: Peer-reviewed
Type: Conference Paper
Rights: Copyright © 2017, Association for Computing Machinery. Deposited with reference to the publisher’s open access archiving policy.
Appears in Collections:Conference Papers & Presentations, Dept. of Computer Science

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