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Edge computing for cyber-physical systems: A Systematic Mapping Study Emphasizing Trustworthiness
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.ORCID iD: 0000-0001-9982-578X
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.ORCID iD: 0000-0002-4300-885X
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics. Ericsson Research, Sweden..ORCID iD: 0000-0001-7448-3381
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2022 (English)In: ACM Transactions on Cyber-Physical Systems, ISSN 2378-962X, Vol. 6, no 3, p. 1-28Article in journal (Refereed) Published
Abstract [en]

Edge computing is projected to have profound implications in the coming decades, proposed to provide solutions for applications such as augmented reality, predictive functionalities, and collaborative Cyber-Physical Systems (CPS). For such applications, edge computing addresses the new computational needs, as well as privacy, availability, and real-time constraints, by providing local high-performance computing capabilities to deal with the limitations and constraints of cloud and embedded systems. Edge computing is today driven by strong market forces stemming from IT/cloud, telecom, and networking - with corresponding multiple interpretations of ”edge computing” (e.g. device edge, network edge, distributed cloud, etc.). Considering the strong drivers for edge-computing and the relative novelty of the field, it becomes important to understand the specific requirements and characteristics of edge-based CPS, and to ensure that research is guided adequately, e.g. avoiding specific gaps.

Our interests lie in the applications of edge computing as part of CPS, where several properties (or attributes) of trustworthiness, including safety, security, and predictability/availability are of particular concern, each facing challenges for the introduction of edge-based CPS. We present the results of a systematic mapping study, a kind of systematic literature survey, investigating the use of edge computing for CPS with a special emphasis on trustworthiness. The main contributions of this study are a detailed description of the current research efforts in edge-based CPS and the identification and discussion of trends and research gaps. The results show that the main body of research in edge-based CPS only to a very limited extent consider key attributes of system trustworthiness, despite many efforts referring to critical CPS and applications like intelligent transportation. More research and industrial efforts will be needed on aspects of trustworthiness of future edge-based CPS including their experimental evaluation. Such research needs to consider the multiple interrelated attributes of trustworthiness including safety, security, and predictability, and new methodologies and architectures to address them. It is further important to provide bridges and collaboration between edge computing and CPS disciplines.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM) , 2022. Vol. 6, no 3, p. 1-28
Keywords [en]
Edge computing; Fog computing; Cloudlet; Mobile edge computing; Cyber-Physical systems; trustworthiness; safety; security; predictability; dependability; critical systems
National Category
Communication Systems Telecommunications Control Engineering Computer Vision and Robotics (Autonomous Systems)
Research subject
Computer Science; Industrial Information and Control Systems; Telecommunication
Identifiers
URN: urn:nbn:se:kth:diva-316312DOI: 10.1145/3539662ISI: 000856728500007Scopus ID: 2-s2.0-85141041347OAI: oai:DiVA.org:kth-316312DiVA, id: diva2:1686853
Projects
TECoSA
Funder
Vinnova, TECoSA
Note

QC 20221031

Available from: 2022-08-11 Created: 2022-08-11 Last updated: 2024-03-18Bibliographically approved

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Gaspar Sánchez, José ManuelJörgensen, NilsTörngren, MartinInam, RafiaBerezovskyi, AndriiFeng, LeiFersman, ElenaRamli, Muhammad RusyadiTan, Kaige

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Gaspar Sánchez, José ManuelJörgensen, NilsTörngren, MartinInam, RafiaBerezovskyi, AndriiFeng, LeiFersman, ElenaRamli, Muhammad RusyadiTan, Kaige
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MechatronicsMachine Design (Dept.)Machine Design (Div.)
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