Publikationer från Malmö universitet
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Towards Supporting IoT System Designers in Edge Computing Deployment Decisions
Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
2021 (engelsk)Licentiatavhandling, med artikler (Annet vitenskapelig)
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.

sted, utgiver, år, opplag, sider
Malmö: Malmö universitet, 2021. , s. 141
Serie
Studies in Computer Science ; 13
Emneord [en]
Internet of Things, Edge computing, Decision Support, Quality Attrib-utes, Metrics, Simulation
HSV kategori
Identifikatorer
URN: urn:nbn:se:mau:diva-37068DOI: 10.24834/isbn.9789178771592ISBN: 978-91-7877-158-5 (tryckt)ISBN: 978-91-7877-159-2 (digital)OAI: oai:DiVA.org:mau-37068DiVA, id: diva2:1506179
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Note: The papers are not included in the fulltext online

Tilgjengelig fra: 2020-12-03 Laget: 2020-12-02 Sist oppdatert: 2024-03-07bibliografisk kontrollert
Delarbeid
1. Analyzing Distributed Deep Neural Network Deployment on Edge and Cloud Nodes in IoT Systems
Åpne denne publikasjonen i ny fane eller vindu >>Analyzing Distributed Deep Neural Network Deployment on Edge and Cloud Nodes in IoT Systems
Vise andre…
2020 (engelsk)Inngår i: IEEE International Conference on Edge Computing (EDGE), Virtual conference, October 18–24, 2020., 2020, s. 59-66Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

For the efficient execution of Deep Neural Networks (DNN) in the Internet of Things, computation tasks can be distributed and deployed on edge nodes. In contrast to deploying all computation to the cloud, the use of Distributed DNN (DDNN) often results in a reduced amount of data that is sent through the network and thus might increase the overall performance of the system. However, finding an appropriate deployment scenario is often a complex task and requires considering several criteria. In this paper, we introduce a multi-criteria decision-making method based on the Analytical Hierarchy Process for the comparison and selection of deployment alternatives. We use the RECAP simulation framework to model and simulate DDNN deployments on different scales to provide a comprehensive assessment of deployments to system designers. In a case study, we apply the method to a smart city scenario where different distributions and deployments of a DNN are analyzed and compared.

Emneord
Edge Computing, Internet of Things, Distributed Deep Neural Networks, Simulation, Smart Cities
HSV kategori
Identifikatorer
urn:nbn:se:mau:diva-37023 (URN)10.1109/EDGE50951.2020.00017 (DOI)000659316400010 ()2-s2.0-85100251401 (Scopus ID)978-1-7281-8254-4 (ISBN)978-1-7281-8255-1 (ISBN)
Konferanse
IEEE International Conference on Edge Computing (EDGE) 2020. 19-23 Oct. 2020. Beijing, China
Tilgjengelig fra: 2020-11-27 Laget: 2020-11-27 Sist oppdatert: 2024-06-17bibliografisk kontrollert
2. Edge Computing Simulators for IoT System Design: An Analysis of Qualities and Metrics
Åpne denne publikasjonen i ny fane eller vindu >>Edge Computing Simulators for IoT System Design: An Analysis of Qualities and Metrics
2019 (engelsk)Inngår i: Future Internet, E-ISSN 1999-5903, Vol. 11, nr 11, s. 235-246Artikkel i tidsskrift (Fagfellevurdert) 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.

sted, utgiver, år, opplag, sider
MDPI, 2019
Emneord
Internet of Things, edge computing, simulation tools, quality characteristics, metrics, ISO/IEC 25023
HSV kategori
Identifikatorer
urn:nbn:se:mau:diva-37014 (URN)10.3390/fi11110235 (DOI)000502277600015 ()2-s2.0-85075344380 (Scopus ID)
Tilgjengelig fra: 2020-11-27 Laget: 2020-11-27 Sist oppdatert: 2024-02-05bibliografisk kontrollert
3. Cloud, Edge, or Both? Towards Decision Support for Designing IoT Applications
Åpne denne publikasjonen i ny fane eller vindu >>Cloud, Edge, or Both? Towards Decision Support for Designing IoT Applications
2018 (engelsk)Inngår i: 2018 Fifth International Conference on Internet of Things: Systems, Management and Security, 2018Konferansepaper, Publicerat paper (Annet vitenskapelig)
Abstract [en]

The rapidly evolving Internet of Things (IoT) includes applications which might generate a huge amount of data, this requires appropriate platforms and support methods. Cloud computing offers attractive computational and storage solutions to cope with these issues. However, sending to centralized servers all the data generated at the edge of the network causes latency, energy consumption, and high bandwidth demand. Performing some computations at the edge of the network, known as Edge computing, and using a hybrid Edge-Cloud architecture can help addressing these challenges. While such architecture may provide new opportunities to distribute IoT applications, making optimal decisions regarding where to deploy the different application components is not an easy and straightforward task for designers. Supporting designers’ decisions by considering key quality attributes impacting them in an Edge-Cloud architecture has not been investigated yet. In this paper, we: explore the importance of decision support for the designers, discuss how different attributes impact the decisions, and describe the required steps toward a decision support framework for IoT application designers.

HSV kategori
Identifikatorer
urn:nbn:se:mau:diva-16827 (URN)10.1109/IoTSMS.2018.8554827 (DOI)000455671800023 ()2-s2.0-85059973173 (Scopus ID)26740 (Lokal ID)978-1-5386-9585-2 (ISBN)26740 (Arkivnummer)26740 (OAI)
Konferanse
The Fifth International Conference on Internet of Things: Systems, Management and Security (IoTSMS 2018), Valencia, Spain (15-18 Oct 2018)
Tilgjengelig fra: 2020-03-30 Laget: 2020-03-30 Sist oppdatert: 2023-12-28bibliografisk kontrollert
4. Quality attributes in edge computing for the Internet of Things: A systematic mapping study
Åpne denne publikasjonen i ny fane eller vindu >>Quality attributes in edge computing for the Internet of Things: A systematic mapping study
2021 (engelsk)Inngår i: Internet of Things: Engineering Cyber Physical Human Systems, E-ISSN 2542-6605, Vol. 13, artikkel-id 100346Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Many Internet of Things (IoT) systems generate a massive amount of data needing to be processed and stored efficiently. Cloud computing solutions are often used to handle these tasks. However, the increasing availability of computational resources close to the edge has prompted the idea of using these for distributed computing and storage. Edge computing may help to improve IoT systems regarding important quality attributes like latency, energy consumption, privacy, and bandwidth utilization. However, deciding where to deploy the various application components is not a straightforward task. This is largely due to the trade-offs between the quality attributes relevant for the application. We have performed a systematic mapping study of 98 articles to investigate which quality attributes have been used in the literature for assessing IoT systems using edge computing. The analysis shows that time behavior and resource utilization are the most frequently used quality attributes; further, response time, turnaround time, and energy consumption are the most used metrics for quantifying these quality attributes. Moreover, simulation is the main tool used for the assessments, and the studied trade-offs are mainly between only two qualities. Finally, we identified a number of research gaps that need further study.

sted, utgiver, år, opplag, sider
Elsevier, 2021
Emneord
Internet of Things, Edge computing, Quality attributes, Metrics, Systematic mapping study
HSV kategori
Identifikatorer
urn:nbn:se:mau:diva-39120 (URN)10.1016/j.iot.2020.100346 (DOI)000695695700015 ()2-s2.0-85106740791 (Scopus ID)
Tilgjengelig fra: 2021-01-13 Laget: 2021-01-13 Sist oppdatert: 2024-02-05bibliografisk kontrollert

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