Networking, IoT, and Their Applications
Table of Contents
Research lead: Dr Idris Ibrahim #
The aim of the InnovateNet Research Group (InNet RG) is to advance networking, IoT, and their applications through innovative research projects. We focus on areas such as Software Defined Network-based MANETs (SDMANET), network monitoring tools and threat detection, generating realistic images from sketches using Generative Adversarial Networks (GANs), integrating advanced wireless technologies and IoT devices into Vehicular Ad Hoc Networks (VANETs), and machine learning-based customer segmentation. Our goal is to develop cutting-edge solutions that improve communication, security, efficiency, and targeting in various domains.
Projects #
1. Software Defined Network-based MANETs (SDMANET) #
SDMANET, an integration of Software-Defined Networking (SDN) with Mobile Ad-Hoc Networks (MANETs), aims to tackle bandwidth, mobility, and power control constraints. Through the amalgamation of SDN nodes with OLSR/BATMAN routing and OpenFlow protocol, it augments flexibility and performance without displacing conventional approaches. Primarily advantageous for 5G and 6G networks, SDMANET holds the potential for enhanced throughput and reduced packet drop rates, representing a noteworthy progression in mobile network architecture.
Project Lead: Rabia Saleh (PhD) res5@hw.ac.uk #
2. Network Monitoring Tool and Threat Detection #
This project aims to design a network monitoring tool to oversee, analyze, and manage computer networks, ensuring reliability and security.
Project Lead: Laura Antunes-Holué (MSc) lma2000@hw.ac.uk #
3. Sketch to Real using GAN (Generative Adversarial Network) #
This project focuses on generating realistic images from sketches using Generative Adversarial Networks, contributing to image-to-image translation tasks
Project Lead: Théo BOUTEMY (MSc) tb2040@hw.ac.uk #
4. Vehicle Ad-Hoc-Networks #
This project explores the integration of advanced wireless technologies and IoT devices into Vehicular Ad Hoc Networks (VANETs) to enhance communication and transportation system efficiency.
Project Lead: Angel Garcia Amigo (MSc) ag2070@hw.ac.uk #
5. Machine Learning Based Customer Segmentation - A Comprehensive Analysis #
This project aims to segment customers based on shopping behavior using machine learning algorithms, improving marketing campaign targeting.