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Fogification of industrial robotic systems: Research challenges
Mälardalen University, School of Business, Society and Engineering, Future Energy Center. ABB AB, Västerås, Sweden.ORCID iD: 0000-0002-4932-7368
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1364-8127
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1687-930X
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2019 (English)In: IoT-Fog 2019 - Proceedings of the 2019 Workshop on Fog Computing and the IoT, Association for Computing Machinery, Inc , 2019, p. 41-45Conference paper, Published paper (Refereed)
Abstract [en]

To meet the demands of future automation systems, the architecture of traditional control systems such as the industrial robotic systems needs to evolve and new architectural paradigms need to be investigated. While cloud-based platforms provide services such as computational resources on demand, they do not address the requirements of real-time performance expected by control applications. Fog computing is a promising new architectural paradigm that complements the cloud-based platform by addressing its limitations. In this paper, we analyse the existing robot system architecture and propose a fog-based solution for industrial robotic systems that addresses the needs of future automation systems. We also propose the use of Time-Sensitive Networking (TSN) services for real-time communication and OPC-UA for information modelling within this architecture. Additionally, we discuss the main research challenges associated with the proposed architecture.

Place, publisher, year, edition, pages
Association for Computing Machinery, Inc , 2019. p. 41-45
Keywords [en]
Automation, Computer architecture, Fog, Industrial research, Internet of things, Robotics, Cloud based platforms, Computational resources, Control applications, Industrial robotic systems, Information modelling, Proposed architectures, Real time performance, Real-time communication, Fog computing
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-43888DOI: 10.1145/3313150.3313225ISI: 000473542200009Scopus ID: 2-s2.0-85066045184ISBN: 9781450366984 (electronic)OAI: oai:DiVA.org:mdh-43888DiVA, id: diva2:1323059
Conference
2019 Workshop on Fog Computing and the IoT, IoT-Fog 2019, 15 April 2019, Montreal, Canada
Available from: 2019-06-11 Created: 2019-06-11 Last updated: 2022-09-06Bibliographically approved
In thesis
1. Integrating Elastic Real-Time Applications on Fog Computing Platforms
Open this publication in new window or tab >>Integrating Elastic Real-Time Applications on Fog Computing Platforms
2022 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Real-time systems such as industrial robots and autonomous navigation vehicles integrate a wide range of algorithms to achieve their functional behavior. In certain systems, these algorithms are deployed on dedicated single-core hardware platforms that exchange information over a real-time network. With the availability of current multi-core platforms, there is growing interest in an integrated architecture where these algorithms can run on a shared hardware platform. In addition, the benefits of virtualization-based cloud and fog architectures for non-real-time applications have prompted discussions about the possibility of achieving similar benefits for real-time systems. Although many useful solutions such as resource reservations and hierarchical scheduling have been proposed to facilitate hardware virtualization for real-time applications, the current state of the art is mainly concerned with applications whose timing requirements can be modelled according to the periodic or the sporadic task model. Since the computational demand of many real-time algorithms can be flexibly adjusted at runtime, e.g., by changing the periods, they can be better abstracted with the elastic task model in the context of virtualized hardware platforms.

Therefore, in this thesis, we first propose a scheduling framework with reservations based on periodic resource supply for real-time elastic applications with single-core workloads, and then extend this solution for applications with multi-core workloads  where reservations are based on the minimum-parallelism model. Since many existing applications run on dedicated single-core platforms, we simultaneously provide a systematic methodology for migrating an existing real-time software application from a single-core to a multi-core platform. In doing so, we focus on recovering the architecture of the existing software and transforming it for implementation on a multi-core platform. Next, we explore the advantages of a fog-based architecture over an existing robot control architecture and identify the key research challenges that must be addressed for the adoption of the fog computing architecture.

Place, publisher, year, edition, pages
Mälardalens universitet, 2022
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 321
National Category
Computer Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-57512 (URN)978-91-7485-547-0 (ISBN)
Presentation
2022-03-30, Delta, Mälardalens universitet, Västerås, 14:00 (English)
Opponent
Supervisors
Available from: 2022-03-01 Created: 2022-02-28 Last updated: 2022-11-08Bibliographically approved

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Salman Shaik, MohammedStruhar, VaclavPapadopoulos, AlessandroBehnam, MorisNolte, Thomas

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