Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses

Green Demand Aware Fog Computing: A Prediction-based Dynamic Resource Provisioning Approach

Ali Kumar, DSNKP, Shah Newaz, SH, Rahman, FH, Lee, GM, Karmakar, G and Au, T-W (2022) Green Demand Aware Fog Computing: A Prediction-based Dynamic Resource Provisioning Approach. Electronics, 11 (4). ISSN 2079-9292

Green Demand Aware Fog Computing A Prediction-based Dynamic Resource Provisioning Approach.pdf - Published Version
Available under License Creative Commons Attribution.

Download (625kB) | Preview


Fog computing has emerged and can potentially be the next paradigm shift by extending cloud services to the edge of the network, bringing resources closer to end user. With its close proximity to end users and distributed nature, latency can be significantly reduced. With the appearance of more and more latency stringent applications, in the near future, we will witness an unprecedented amount of demand for fog computing. Undoubtedly, this will lead to the rise of energy footprint of the network edge and access segment. To reduce energy consumption in fog computing while not compromising their performance, this paper proposes Green Demand Aware Fog Computing (GDAFC) solution. Our solution uses a prediction technique to identify the working fog nodes (nodes serve when request arrives), standby fog nodes (nodes take over when the computational capacity of the working fog nodes is no longer sufficient), and idle fog nodes in a fog computing infrastructure. Additionally, it assigns an appropriate sleep interval for the fog nodes, taking into account the delay requirement of the applications. Results obtained based on the mathematical formulation show our solution can save energy up to 65% without deteriorating the delay requirement performance.

Item Type: Article
Uncontrolled Keywords: 0906 Electrical and Electronic Engineering
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics. Nuclear engineering
Divisions: Computer Science & Mathematics
Publisher: MDPI
Date Deposited: 11 Feb 2022 11:24
Last Modified: 31 Mar 2022 10:45
DOI or ID number: 10.3390/electronics11040608
URI: https://researchonline.ljmu.ac.uk/id/eprint/16276
View Item View Item