Classification of resource management approaches in fog/edge paradigm and future research prospects: a systematic review

Kansal, Puneet; Kumar, Manoj; Verma, Om Prakash

doi:10.1007/s11227-022-04338-1

Cited by 17 publications

(7 citation statements)

References 374 publications

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“…They only focused on computational offloading and mobility management with AI methods and only discussed a few AI-based works for these issues. Kansal et al [32] presented a review of data-driven approaches for fog management issues. They are classified based on the technology used, QoS factors, and data-driven strategies.…”

Section: Related Surveys and Contributionsmentioning

confidence: 99%

“…AI-based techniques used to solve resource management problems in Fog/Edge computing can be summarized as Deep Learning (DL), Machine Learning (ML), Reinforcement Learning (RL), and Deep Reinforcement Learning (DRL). AI-based techniques are very effective in dynamic resource scheduling [32]. In particular, DRL has been shown to be very successful in dynamic complex problems and dynamic task offloading [32].…”

Section: J O U R N a L P R E -P R O O Fmentioning

confidence: 99%

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AI-based fog and edge computing: A systematic review, taxonomy and future directions

et al. 2023

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Section: Related Surveys and Contributionsmentioning

confidence: 99%

Section: J O U R N a L P R E -P R O O Fmentioning

confidence: 99%

AI-based fog and edge computing: A systematic review, taxonomy and future directions

et al. 2023

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“…In recent years, there have been attempts to introduce serverless computing in the context of FC and edge computing paradigms, such as Fog Function [ 59 ], Edgeless [ 60 ]. However, to be able to simulate the scenarios of serverless FC, considered simulators need to focus more on resource management aspects such as resource allocation, scheduling, and scaling techniques based on the incoming user demands [ 61 , 62 , 63 ].…”

Section: Open Issues and Challengesmentioning

confidence: 99%

Simulation Tools for Fog Computing: A Comparative Analysis

Fahimullah

Guillaume

Ahvar

et al. 2023

Sensors

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Fog Computing (FC) was introduced to offer resources closer to the users. Researchers propose different solutions to make FC mature and use simulators for evaluating their solutions at early stages. In this paper, we compare different FC simulators based on their technical and non-technical characteristics. In addition, a practical comparison is conducted to compare the three main FC simulators based on their performance such as execution time, CPU, and memory usage for running different applications. The analysis can be helpful for researchers to select the appropriate simulator and platform to evaluate their solutions on different use cases. Furthermore, open issues and challenges for FC simulators are discussed that require attention and need to be addressed in the future.

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“…Kansal et al [15] presented a systematic literature review of the resource management approaches in fog/edge paradigm.…”

Section: B Related Workmentioning

confidence: 99%

Cloud Continuum: The Definition

Moreschini

Pecorelli

et al. 2022

IEEE Access

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The cloud continuum concept has drawn increasing attention from practitioners, academics, and funding agencies and been adopted progressively. However, the concept remains mired in various definitions with different studies providing contrasting descriptions. Therefore, to understand the concept of cloud continuum and to provide its definition, in this work we conduct a systematic mapping study of the literature investigating the different definitions, how they evolved, and where does the cloud continue. The main outcome of this work is a complete definition that merges all the common aspects of cloud continuum, which enables practitioners and researchers to better understand what cloud continuum is.INDEX TERMS Cloud continuum, edge, Fog.

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Classification of resource management approaches in fog/edge paradigm and future research prospects: a systematic review

Cited by 17 publications

References 374 publications

AI-based fog and edge computing: A systematic review, taxonomy and future directions

AI-based fog and edge computing: A systematic review, taxonomy and future directions

Simulation Tools for Fog Computing: A Comparative Analysis

Cloud Continuum: The Definition

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