Edge / Fog Analytics for IoT Architectures

Project Overview

Explores fog and edge computing architectures for IoT, evaluating distributed analytics platforms and their applications.

Fog computing is an architecture that uses one or more collaborative end-user clients or near-user edge devices to carry out a substantial amount of storage and processing rather than relying on centralised cloud infrastructure. This approach deploys computing nodes throughout IoT networks—on factory floors, in vehicles, on power poles, and at oil rigs—to analyse data locally, reducing latency and network traffic while enhancing security and privacy by avoiding centralised data storage.

This project evaluated fog and edge computing architectures, middleware, and distributed analytics approaches for edge-centric IoT deployments. The research explored how to push computation closer to data sources, enabling real-time decision making in scenarios where cloud connectivity is limited or latency requirements are stringent.

Team

Charith Perera

Prem Jayaraman

Athanasios V. Vasilakos

Rajiv Ranjan

Stephan Reiff-Marganiec

Julio C. Estrella

Yongrui Qin

Muhammad Habib ur Rehman

Albert Y. Zomaya

Chi Harold Liu

Dumidu Talagala

Min Chen

Wilfrido Moreno

Ozgur Yurur

Badraddin Alturki

Outcomes