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Edge-Oriented Computing: A Survey on Research and Use Cases

Author

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  • Nour Alhuda Sulieman

    (Dipartimento di Scienze Matematiche e Informatiche, Scienze Fisiche e Scienze Della Terra, Università di Messina, Piazza Pugliatti 1, 98122 Messina, Italy)

  • Lorenzo Ricciardi Celsi

    (ELIS Innovation Hub, via Sandro Sandri 45-81, 00159 Roma, Italy)

  • Wei Li

    (Centre for Distributed and High Performance Computing, University of Sydney, Sydney, NSW 2006, Australia)

  • Albert Zomaya

    (Centre for Distributed and High Performance Computing, University of Sydney, Sydney, NSW 2006, Australia)

  • Massimo Villari

    (Dipartimento di Scienze Matematiche e Informatiche, Scienze Fisiche e Scienze Della Terra, Università di Messina, Piazza Pugliatti 1, 98122 Messina, Italy)

Abstract

Edge computing is a distributed computing paradigm such that client data are processed at the periphery of the network, as close as possible to the originating source. Since the 21st century has come to be known as the century of data due to the rapid increase in the quantity of exchanged data worldwide (especially in smart city applications such as autonomous vehicles), collecting and processing such data from sensors and Internet of Things devices operating in real time from remote locations and inhospitable operating environments almost anywhere in the world is a relevant emerging need. Indeed, edge computing is reshaping information technology and business computing. In this respect, the paper is aimed at providing a comprehensive overview of what edge computing is as well as the most relevant edge use cases, tradeoffs, and implementation considerations. In particular, this review article is focused on highlighting (i) the most recent trends relative to edge computing emerging in the research field and (ii) the main businesses that are taking operations at the edge as well as the most used edge computing platforms (both proprietary and open source). First, the paper summarizes the concept of edge computing and compares it with cloud computing. After that, we discuss the challenges of optimal server placement, data security in edge networks, hybrid edge-cloud computing, simulation platforms for edge computing, and state-of-the-art improved edge networks. Finally, we explain the edge computing applications to 5G/6G networks and industrial internet of things. Several studies review a set of attractive edge features, system architectures, and edge application platforms that impact different industry sectors. The experimental results achieved in the cited works are reported in order to prove how edge computing improves the efficiency of Internet of Things networks. On the other hand, the work highlights possible vulnerabilities and open issues emerging in the context of edge computing architectures, thus proposing future directions to be investigated.

Suggested Citation

  • Nour Alhuda Sulieman & Lorenzo Ricciardi Celsi & Wei Li & Albert Zomaya & Massimo Villari, 2022. "Edge-Oriented Computing: A Survey on Research and Use Cases," Energies, MDPI, vol. 15(2), pages 1-28, January.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:2:p:452-:d:721094
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    References listed on IDEAS

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    1. Christina Kakderi & Panagiotis Tsarchopoulos & Nicos Komninos & Anastasia Panori, 2019. "Smart Cities on the Cloud," Progress in IS, in: Anastasia Stratigea & Dimitris Kavroudakis (ed.), Mediterranean Cities and Island Communities, chapter 0, pages 57-80, Springer.
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    Cited by:

    1. Rossana Coccia & Veronica Tonti & Chiara Germanò & Francesco Palone & Lorenzo Papi & Lorenzo Ricciardi Celsi, 2022. "A Multi-Variable DTR Algorithm for the Estimation of Conductor Temperature and Ampacity on HV Overhead Lines by IoT Data Sensors," Energies, MDPI, vol. 15(7), pages 1-13, April.

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