Edge/Fog Computing Technologies for IoT Infrastructure II-Reference-Cited by-同舟云学术

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Edge/Fog Computing Technologies for IoT Infrastructure II

Published:2023-04-13 Issue:8 Volume:23 Page:3953
ISSN:1424-8220
Container-title:Sensors
language:en
Short-container-title:Sensors

Author:

Kim Taehong¹^ORCID,Yoo Seong-eun²^ORCID,Kim Youngsoo³^ORCID

Affiliation:

1. School of Information and Communication Engineering, Chungbuk National University, Cheongju 28644, Republic of Korea

2. School of Artificial Intelligence, Daegu University, Gyeongsan 38453, Republic of Korea

3. Department of Artificial Intelligence, Jeonju University, Jeonju 55069, Republic of Korea

Abstract

The prevalence of smart devices and cloud computing has led to an explosion in the amount of data generated by IoT devices [...]

Funder

National Research Foundation of Korea (NRF) grant funded by the Korea government

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Link

https://www.mdpi.com/1424-8220/23/8/3953/pdf

Reference7 articles.

1. Liutkevičius, A., Morkevičius, N., Venčkauskas, A., and Toldinas, J. (2022). Distributed Agent-Based Orchestrator Model for Fog Computing. Sensors, 22.

2. Hossain, M.D., Sultana, T., Hossain, M.A., Layek, M.A., Hossain, M.I., Sone, P.P., Lee, G.-W., and Huh, E.-N. (2022). Dynamic Task Offloading for Cloud-Assisted Vehicular Edge Computing Networks: A Non-Cooperative Game Theoretic Approach. Sensors, 22.

3. Liu, X., Zhao, X., Liu, G., Huang, F., Huang, T., and Wu, Y. (2022). Collaborative Task Offloading and Service Caching Strategy for Mobile Edge Computing. Sensors, 22.

4. Kim, S.-H., and Kim, T. (2023). Local Scheduling in KubeEdge-Based Edge Computing Environment. Sensors, 23.

5. Lim, J. (2022). Latency-Aware Task Scheduling for IoT Applications Based on Artificial Intelligence with Partitioning in Small-Scale Fog Computing Environments. Sensors, 22.

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