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Edge Computing Simulators for IoT System Design: An Analysis of Qualities and Metrics
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0002-8209-0921
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0003-0998-6585
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0003-0326-0556
2019 (English)In: Future Internet, E-ISSN 1999-5903, Vol. 11, no 11, p. 235-246Article in journal (Refereed) Published
Abstract [en]

The deployment of Internet of Things (IoT) applications is complex since many quality characteristics should be taken into account, for example, performance, reliability, and security. In this study, we investigate to what extent the current edge computing simulators support the analysis of qualities that are relevant to IoT architects who are designing an IoT system. We first identify the quality characteristics and metrics that can be evaluated through simulation. Then, we study the available simulators in order to assess which of the identified qualities they support. The results show that while several simulation tools for edge computing have been proposed, they focus on a few qualities, such as time behavior and resource utilization. Most of the identified qualities are not considered and we suggest future directions for further investigation to provide appropriate support for IoT architects.

Place, publisher, year, edition, pages
MDPI, 2019. Vol. 11, no 11, p. 235-246
Keywords [en]
Internet of Things, edge computing, simulation tools, quality characteristics, metrics, ISO/IEC 25023
National Category
Computer Systems Communication Systems Embedded Systems
Identifiers
URN: urn:nbn:se:mau:diva-37014DOI: 10.3390/fi11110235ISI: 000502277600015Scopus ID: 2-s2.0-85075344380OAI: oai:DiVA.org:mau-37014DiVA, id: diva2:1504451
Available from: 2020-11-27 Created: 2020-11-27 Last updated: 2024-02-05Bibliographically approved
In thesis
1. Towards Supporting IoT System Designers in Edge Computing Deployment Decisions
Open this publication in new window or tab >>Towards Supporting IoT System Designers in Edge Computing Deployment Decisions
2021 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The rapidly evolving Internet of Things (IoT) systems demands addressing new requirements. This particularly needs efficient deployment of IoT systems to meet the quality requirements such as latency, energy consumption, privacy, and bandwidth utilization. The increasing availability of computational resources close to the edge has prompted the idea of using these for distributed computing and storage, known as edge computing. Edge computing may help and complement cloud computing to facilitate deployment of IoT systems and improve their quality. However, deciding where to deploy the various application components is not a straightforward task, and IoT system designer should be supported for the decision.

To support the designers, in this thesis we focused on the system qualities, and aimed for three main contributions. First, by reviewing the literature, we identified the relevant and most used qualities and metrics. Moreover, to analyse how computer simulation can be used as a supporting tool, we investigated the edge computing simulators, and in particular the metrics they provide for modeling and analyzing IoT systems in edge computing. Finally, we introduced a method to represent how multiple qualities can be considered in the decision. In particular, we considered distributing Deep Neural Network layers as a use case and raked the deployment options by measuring the relevant metrics via simulation.

Place, publisher, year, edition, pages
Malmö: Malmö universitet, 2021. p. 141
Series
Studies in Computer Science ; 13
Keywords
Internet of Things, Edge computing, Decision Support, Quality Attrib-utes, Metrics, Simulation
National Category
Communication Systems Other Electrical Engineering, Electronic Engineering, Information Engineering Computer Systems
Identifiers
urn:nbn:se:mau:diva-37068 (URN)10.24834/isbn.9789178771592 (DOI)978-91-7877-158-5 (ISBN)978-91-7877-159-2 (ISBN)
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Note: The papers are not included in the fulltext online

Available from: 2020-12-03 Created: 2020-12-02 Last updated: 2024-03-07Bibliographically approved

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Ashouri, MajidLorig, FabianDavidsson, PaulSpalazzese, Romina

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