Fog Computing for Sustainable Smart Cities

Abstract

The Internet of Things (IoT) aims to connect billions of smart objects to the Internet, which can bring a promising future to smart cities. These objects are expected to generate large amounts of data and send the data to the cloud for further processing, specially for knowledge discovery, in order that appropriate actions can be taken. However, in reality sensing all possible data items captured by a smart object and then sending the complete captured data to the cloud is less useful. Further, such an approach would also lead to resource wastage (e.g. network, storage, etc.). The Fog (Edge) computing paradigm has been proposed to counterpart the weakness by pushing processes of knowledge discovery using data analytics to the edges. However, edge devices have limited computational capabilities. Due to inherited strengths and weaknesses, neither Cloud computing nor Fog computing paradigm addresses these challenges alone. Therefore, both paradigms need to work together in order to build an sustainable IoT infrastructure for smart cities. In this paper, we review existing approaches that have been proposed to tackle the challenges in the Fog computing domain. Specifically, we describe several inspiring use case scenarios of Fog computing, identify ten key characteristics and common features of Fog computing, and compare more than 30 existing research efforts in this domain. Based on our review, we further identify several major functionalities that ideal Fog computing platforms should support and a number of open challenges towards implementing them, so as to shed light on future research directions on realizing Fog computing for building sustainable smart cities.

Elucidating the challenges for the praxis of fog computing: An aspect‐based study

“…Tang et al proposed a fog computing‐based big data analysis framework for smart cities. The proposed hierarchical framework provides responses in real time by applying analytics operations on the data generated from millions of devices deployed across the city . Gia et al introduced fog computing in the health‐care sector for real‐time monitoring of human health using IoT devices.…”

Energy-Efficient Learning System Using Web-Based Panoramic Virtual Photoreality for Interactive Construction Safety Education

“…On the contrary, our literature review revealed that Web-based applications achieve low energy consumption as a result of their on-demand and low-complexity features. The rationale behind this is that almost all of their heavy workloads are offloaded and performed remotely in the central server side [25,26]. In addition, the recent emergence of mobile edge/cloud computing technologies has provided effective cloudized computation infrastructure to promote the Web-based application approaches [27][28][29].…”

Computational Viability of Fog Methodologies in IoT Enabled Smart City Architectures-A Smart Grid Case Study

“…The prevalent cloud models are not intended to handle the seven unprecedented V's (Volume, Velocity, Variety, Variability, Veracity, Visualization and Value) in the data generated by IoT architectures and coupling the whole universe of -things‖ or -objects‖ directly to the cloud is nearly unfeasible [10]. Fog computing approaches seem to be the preeminent preference for computations at the extreme edges such as vehicles, roadways, charging station etc [10]- [13]. However installation of fogs (mini data centers) everywhere across the edges of the networks and entities may not be cost productive.…”