Energy Efficient Service Placement for IoT Networks

TL;DR

This paper explores how dynamic service placement in layered IoT architectures can optimize energy efficiency across fog and cloud layers, based on simulation results.

Contribution

It introduces adaptive service placement strategies tailored for IoT networks to enhance energy efficiency, supported by simulation analysis.

Findings

Access Fog is optimal for single requests.

Metro Fog efficiently manages higher device demands.

Adaptive strategies improve overall energy efficiency.

Abstract

In recent years, there has been a significant expansion in the Internet of Things (IoT), with a growing number of devices being connected to the internet. This has led to an increase in data collection and analysis as well as the development of new technologies and applications. The rise of IoT has also brought about new challenges, such as security concerns and energy efficiency. This study investigates a layered IoT architecture that combines fog and cloud computing, aiming to assess the impact of service placement on energy efficiency. Through simulations, we analyse energy use across Access Fog, Metro Fog, and Cloud Data Centre layers for different IoT request volumes. Findings indicate that Access Fog is optimal for single requests, while Metro Fog efficiently manages higher demands from multiple devices. The study emphasizes the need for adaptive service deployment, responsive to network load variations, to improve energy efficiency. Hence, we propose the implementation of dynamic service placement strategies within Internet of Things (IoT) environments.