A Systemic IoT-Fog-Cloud Architecture for Big-Data Analytics and Cyber Security Systems: A Review of Fog Computing

TL;DR

This paper reviews a layered IoT-Fog-Cloud architecture designed to enhance big-data analytics and cybersecurity, addressing current cloud limitations through fog computing at network edges.

Contribution

It proposes a systemic architecture clarifying interactions among IoT, Fog, and Cloud layers for improved analytics and security, and reviews related challenges and solutions.

Findings

Identifies security challenges in fog computing environments.

Highlights the benefits of edge computing for latency reduction.

Outlines future research directions in IoT-Fog-Cloud systems.

Abstract

Abstract--- With the rapid growth of the Internet of Things (IoT), current Cloud systems face various drawbacks such as lack of mobility support, location-awareness, geo-distribution, high latency, as well as cyber threats. Fog/Edge computing has been proposed for addressing some of the drawbacks, as it enables computing resources at the network's edges and it locally offers big-data analytics rather than transmitting them to the Cloud. The Fog is defined as a Cloud-like system having similar functions, including software-, platform- and infrastructure-as services. The deployment of Fog applications faces various security issues related to virtualisation, network monitoring, data protection and attack detection. This paper proposes a systemic IoT-Fog-Cloud architecture that clarifies the interactions between the three layers of IoT, Fog and Cloud for effectively implementing big-data analytics and cyber security applications. It also reviews security challenges, solutions and future research directions in the architecture.