Energy Efficient Cloud-Fog Architecture

TL;DR

This paper examines the energy consumption challenges of cloud-fog computing architectures, analyzing factors affecting power use and proposing VM placement strategies for energy efficiency.

Contribution

It introduces an analysis of energy consumption in cloud-fog architectures and proposes VM placement optimization for improved energy efficiency.

Findings

Energy consumption is significantly impacted by VM placement strategies.

Different scenarios affect the energy efficiency of cloud-fog architectures.

Numerical results demonstrate potential energy savings through optimized VM placement.

Abstract

The advancements of cloud computing came as a radical transformation in the way Information and Communication Technology (ICT) services are deployed and maintained. Cloud computing provides ubiquitous on-demand access to an Internet-based pool of processing, storage, and communication resources offered to a large set of geographically distributed users. As the cloud computing infrastructure grows and demand increases, the need for a new breed of on-demand computing that can efficiently maintain Quality of Service (QoS) requirements has increased. Fog computing was proposed to address the limitations of cloud computing, in terms of delay and high bandwidth requirements, by extending the on-demand resources of clouds to the edge of the network bringing them closer to the users. The massive growth and wide use of cloud-fog services have created serious power consumption concerns. This article delves into the energy consumption of cloud-fog services by raising headline questions related to; how significant the problem itself is, how different conditions/scenarios affect the energy consumption of the architecture, and how to orchestrate the use of the architecture in an energy-efficient manner. We start by summarizing the cloud-fog architecture including different communication and computing layers. Additionally, we give a brief overview of the role of Virtual Machine (VM) placement in optimally using cloud-fog resources in a dynamic manner. Then, we present the problem of energy efficient VMs placement and provide numerical results.