Evidence map›Paper›PMID 34690529›Full record

ArticleMultimedia tools and applications2022

Towards effective offloading mechanisms in fog computing.

Maryam Sheikh Sofla, Mostafa Haghi Kashani, Ebrahim Mahdipour, Reza Faghih Mirzaee

Abstract read
In one paragraph

Article in Multimedia tools and applications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Fog computing: a platform for big-data marketing analytics.Frontiers in artificial intelligence · 2023
    Review
  4. Article
  5. Fog-based healthcare systems: A systematic review.Multimedia tools and applications · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Maryam Sheikh SoflaDepartment of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Mostafa Haghi KashaniDepartment of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Ebrahim MahdipourDepartment of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.ORCID 0000-0003-3746-7678
Reza Faghih MirzaeeDepartment of Computer Engineering, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fog computing is considered a formidable next-generation complement to cloud computing. Nowadays, in light of the dramatic rise in the number of IoT devices, several problems have been raised in cloud architectures. By introducing fog computing as a mediate layer between the user devices and the cloud, one can extend cloud computing's processing and storage capability. Offloading can be utilized as a mechanism that transfers computations, data, and energy consumption from the resource-limited user devices to resource-rich fog/cloud layers to achieve an optimal experience in the quality of applications and improve the system performance. This paper provides a systematic and comprehensive study to evaluate fog offloading mechanisms' current and recent works. Each selected paper's pros and cons are explored and analyzed to state and address the present potentialities and issues of offloading mechanisms in a fog environment efficiently. We classify offloading mechanisms in a fog system into four groups, including computation-based, energy-based, storage-based, and hybrid approaches. Furthermore, this paper explores offloading metrics, applied algorithms, and evaluation methods related to the chosen offloading mechanisms in fog systems. Additionally, the open challenges and future trends derived from the reviewed studies are discussed.

Indexed as

Fog computingInternet of things (IoT)OffloadingQuality of service (QoS)

Identifiers

PMID34690529
PMCPMC8526054

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.