Evidence map›Paper›PMID 37631678›Full record

ArticleSensors (Basel, Switzerland)2023

Microservice Application Scheduling in Multi-Tiered Fog-Computing-Enabled IoT.

Maria Ashraf, Muhammad Shiraz, Almas Abbasi, Omar Alqahtani, Gran Badshah, Ayodele Lasisi

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.4field-weighted citation impact, top 18% of its field
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

1 citing paper in PubMed, 7 citations in OpenAlex.

  1. 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

6 authors at 3 institutions in 2 countries.

Maria AshrafDepartment of Computer Science, Faculty of Computing and Information Technology, International Islamic University, Islamabad 44000, Pakistan.ORCID 0000-0002-8306-2762
Muhammad ShirazDepartment of Computer Science, Federal Urdu University of Arts, Science and Technology, Islamabad 44000, Pakistan.ORCID 0000-0002-0149-7413
Almas AbbasiDepartment of Computer Science, Faculty of Computing and Information Technology, International Islamic University, Islamabad 44000, Pakistan.
Omar AlqahtaniDepartment of Computer Science, King Khalid University, Abha 61413, Saudi Arabia.
Gran BadshahDepartment of Computer Science, King Khalid University, Abha 61413, Saudi Arabia.ORCID 0000-0002-1060-580X
Ayodele LasisiDepartment of Computer Science, King Khalid University, Abha 61413, Saudi Arabia.
King Khalid University · SAInternational Islamic University, Islamabad · PKFederal Urdu University · PK

Funding

Deanship of Scientific Research at King Khalid University RGP2/394/44Funder details will be provided later. Grant number will be provide later.
6 · The paper itself

Abstract

Fog computing extends mobile cloud computing facilities at the network edge, yielding low-latency application execution. To supplement cloud services, computationally intensive applications can be distributed on resource-constrained mobile devices by leveraging underutilized nearby resources to meet the latency and bandwidth requirements of application execution. Building upon this premise, it is necessary to investigate idle or underutilized resources that are present at the edge of the network. The utilization of a microservice architecture in IoT application development, with its increased granularity in service breakdown, provides opportunities for improved scalability, maintainability, and extensibility. In this research, the proposed schedule tackles the latency requirements of applications by identifying suitable upward migration of microservices within a multi-tiered fog computing infrastructure. This approach enables optimal utilization of network edge resources. Experimental validation is performed using the iFogSim2 simulator and the results are compared with existing baselines. The results demonstrate that compared to the edgewards approach, our proposed technique significantly improves the latency requirements of application execution, network usage, and energy consumption by 66.92%, 69.83%, and 4.16%, respectively.

Indexed as

constrained devicesdistributed application executionfog computingInternet of Thingsmicroservice application schedulingservice delay

Identifiers

PMID37631678
PMCPMC10459426
OpenAlexW4385811802

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.