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Cited by 236IoT and Edge/Fog ComputingCloud Computing and Resource ManagementEnergy Efficiency in Computing

Serverless Edge Computing: Vision and Challenges

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Aslanpour, Mohammad S., Toosi, Adel N., Cicconetti, Claudio, Javadi, Bahman, Sbarski, Peter, Taibi, Davide, Assuncao, Marcos, Gill, Sukhpal Singh +2 more·2021·2021 Australasian Computer Science Week Multiconference
DOI 10.1145/3437378.3444367
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Abstract

Born from a need for a pure “pay-per-use” model and highly scalable platform, the “Serverless” paradigm emerged and has the potential to become a dominant way of building cloud applications. Although it was originally designed for cloud environments, Serverless is finding its position in the Edge Computing landscape, aiming to bring computational resources closer to the data source. That is, Serverless is crossing cloud borders to assess its merits in Edge computing, whose principal partner will be the Internet of Things (IoT) applications. This move sounds promising as Serverless brings particular benefits such as eliminating always-on services causing high electricity usage, for instance. However, the community is still hesitant to uptake Serverless Edge Computing because of the cloud-driven design of current Serverless platforms, and distinctive characteristics of edge landscape and IoT applications. In this paper, we evaluate both sides to shed light on the Serverless new territory. Our in-depth analysis promotes a broad vision for bringing Serverless to the Edge Computing. It also issues major challenges for Serverless to be met before entering Edge computing.

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  • Fog computing is distinguished from cloudlets by its explicit linkage to fixed devices with connectivity and intelligent data analyzing and processing capabilities.

    “This explicit linkage to fixed devices with connectivity and intelligent data analysing and data processing capabilities clearly distinguished FC from cloudlets [7].”

    From Edge AI: A survey (2023) · cites this paper as [7]

    Section 2.2 (page unavailable) describes fog computing as edge computing in which IoT devices can gain computational capabilities. Section 3.0.1 (page unavailable) also describes edge nodes with communication and computation capabilities. Neither passage says fog computing is explicitly linked to fixed devices or distinguishes it from cloudlets; searches for “cloudlet” and the claimed distinction found no such comparison. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

  • Analyzing data close to the device that collected it can make the difference between averting disaster and a cascading system failure.

    “Analysing data close to the device that collected the data can make the difference between averting disaster and a cascading system failure”

    From Edge AI: A survey (2023) · cites this paper as [6]

    Section 2.2 says computing closer to data sources helps meet low-latency and real-time requirements, and §4.5 says mission-critical IoT applications may fail to react promptly without rapid processing. Section 5.10 warns that unhandled function or edge-node failures can cause a disaster, but it does not say that analyzing data near its collecting device averts a cascading system failure. Page numbers were not available in our copy. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

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Authors
Aslanpour, M. S., Toosi, A. N., Cicconetti, C., Javadi, B., Sbarski, P., Taibi, D., Assuncao, M., Gill, S. S., Gaire, R., & Dustdar, S.
Affiliations
  • Commonwealth Scientific and Industrial Research Organisation (AU)
  • Monash University (AU)
  • National Research Council (IT)
  • Western Sydney University (AU)
  • A Cloud Guru, Australia
  • Tampere University (FI)
  • Inria ENS de Lyon, France
  • Queen Mary University of London (GB)
  • TU Wien (AT)
ORCID
Venue
2021 Australasian Computer Science Week Multiconference
Publisher
ACM
Published
2021-02
Pages
1-10
DOI
10.1145/3437378.3444367
OpenAlex
W3126507566
Cited by
236
References
0
Citations by year
2026: 19 · 2025: 43 · 2024: 52 · 2023: 46 · 2022: 46 · 2021: 30
FWCI
40.21
Type
conference paper
Language
en
Open access
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)
Locations
  • Australasian Computer Science Week Multiconference (ACSW) (publishedVersion)
  • Queen Mary Research Online (Queen Mary University of London) (submittedVersion)
  • Espace ÉTS (ETS) (submittedVersion)
  • Minerva Access (University of Melbourne) (submittedVersion)
  • Tampere University Institutional Repository (Tampere University) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
  • Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
  • Physical Sciences › Computer Science › Hardware and Architecture › Energy Efficiency in Computing
Keywords
serverless computing, edge computing, Internet of Things, cloud computing, pay-per-use, scalability, energy efficiency, cloud-edge integration, IoT applications

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