eCite Digital Repository

Sustainability analysis for fog nodes with renewable energy supplies


Jiang, J and Gao, L and Jin, J and Luan, TH and Yu, S and Xiang, Y and Garg, S, Sustainability analysis for fog nodes with renewable energy supplies, IEEE Internet of Things Journal, 6, (4) pp. 6725-6735. ISSN 2327-4662 (2019) [Refereed Article]


Copyright Statement

Copyright 2019 IEEE Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Official URL:

DOI: doi:10.1109/JIOT.2019.2910875


There is a growing interest in the use of renewable energy sources to power fog networks in order to mitigate the detrimental effects of conventional energy production. However, renewable energy sources, such as solar and wind, are by nature unstable in their availability and capacity. The dynamics of energy supply hence impose new challenges for network planning and resource management. In this paper, the sustainable performance of a fog node powered by renewable energy sources is studied. We develop a generic analytical model to study the energy sustainability of fog nodes powered by renewable energy sources, by generalizing the Leaky Bucket model to shape and police traffic source for rate-based congestion control in high-speed fog networks. Based on the closed-form solutions of energy buffer analysis, i.e., the energy depletion probability and mean energy length, we study the energy sustainability in two special but real-happening scenarios. The experimental results show that with proper design the Leaky Bucket model effectively reflects the energy sustainability of data traffic in fog networks. Numerical results also reveal that the model performance is sensitive to certain traffic source characteristics in fog networks.

Item Details

Item Type:Refereed Article
Keywords:energy efficient, edge computing, cloud computing, fog computing
Research Division:Information and Computing Sciences
Research Group:Distributed computing and systems software
Research Field:Distributed systems and algorithms
Objective Division:Environmental Policy, Climate Change and Natural Hazards
Objective Group:Mitigation of climate change
Objective Field:Management of greenhouse gas emissions from information and communication services
UTAS Author:Garg, S (Dr Saurabh Garg)
ID Code:131953
Year Published:2019
Web of Science® Times Cited:10
Deposited By:Information and Communication Technology
Deposited On:2019-04-15
Last Modified:2020-09-10

Repository Staff Only: item control page