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PrEstoCloud: A Novel Framework for Data-Intensive Multi-Cloud, Fog, and Edge Function-as-a-Service Applications

Author

Listed:
  • Yiannis Verginadis

    (Athens University of Economics and Business, Greece)

  • Dimitris Apostolou

    (University of Piraeus, Greece)

  • Salman Taherizadeh

    (Joseph Stefan Institute, Slovenia)

  • Ioannis Ledakis

    (Ubitech, Greece)

  • Gregoris Mentzas

    (National Technical University of Athens, Greece)

  • Andreas Tsagkaropoulos

    (National Technical University of Athens, Greece)

  • Nikos Papageorgiou

    (National Technical University of Athens, Greece)

  • Fotis Paraskevopoulos

    (National Technical University of Athens, Greece)

Abstract

Fog computing extends multi-cloud computing by enabling services or application functions to be hosted close to their data sources. To take advantage of the capabilities of fog computing, serverless and the function-as-a-service (FaaS) software engineering paradigms allow for the flexible deployment of applications on multi-cloud, fog, and edge resources. This article reviews prominent fog computing frameworks and discusses some of the challenges and requirements of FaaS-enabled applications. Moreover, it proposes a novel framework able to dynamically manage multi-cloud, fog, and edge resources and to deploy data-intensive applications developed using the FaaS paradigm. The proposed framework leverages the FaaS paradigm in a way that improves the average service response time of data-intensive applications by a factor of three regardless of the underlying multi-cloud, fog, and edge resource infrastructure.

Suggested Citation

  • Yiannis Verginadis & Dimitris Apostolou & Salman Taherizadeh & Ioannis Ledakis & Gregoris Mentzas & Andreas Tsagkaropoulos & Nikos Papageorgiou & Fotis Paraskevopoulos, 2021. "PrEstoCloud: A Novel Framework for Data-Intensive Multi-Cloud, Fog, and Edge Function-as-a-Service Applications," Information Resources Management Journal (IRMJ), IGI Global, vol. 34(1), pages 66-85, January.
    • Handle: RePEc:igg:rmj000:v:34:y:2021:i:1:p:66-85
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