58 citations · 193 across the 28 of their papers we have counts for
14 papers · 1 filter
Q-CSM: Q-Learning-based Cognitive Service Management in Heterogeneous IoT Networks
Kubra Duran, Mehmet Ozdem, Kerem Gursu +1
The dramatic increase in the number of smart services and their diversity poses a significant challenge in Internet of Things (IoT) networks: heterogeneity. This causes significant…
Generative AI-enabled Digital Twins for 6G-enhanced Smart Cities
Kubra Duran, Lal Verda Cakir, Mehmet Ozdem +2
6G networks are envisioned to enable a wide range of applications, such as autonomous vehicles and smart cities. However, this rapid expansion of network topologies makes the manag…
AI-based traffic analysis in digital twin networks
Sarah Al-Shareeda, Khayal Huseynov, Lal Verda Cakir +3
In today's networked world, Digital Twin Networks (DTNs) are revolutionizing how we understand and optimize physical networks. These networks, also known as 'Digital Twin Networks…
Optimized Resource Allocation for Cloud-Native 6G Networks: Zero-Touch ML Models in Microservices-based VNF Deployments
Swarna Bindu Chetty, Avishek Nag, Ahmed Al-Tahmeesschi +4
6G, the next generation of mobile networks, is set to offer even higher data rates, ultra-reliability, and lower latency than 5G. New 6G services will increase the load and dynamis…
DTRAN: A Special Use Case of RAN Optimization using Digital Twin
Caglar Tunc, Kubra Duran, Buse Bilgin +2
The emergence of beyond 5G (B5G) and 6G networks underscores the critical role of advanced computer-aided tools, such as network digital twins (DTs), in fostering autonomous networ…
Real-Time Digital Twin Platform: A Case Study on Core Network Selection in Aeronautical Ad-Hoc Networks
Lal Verda Cakir, Mihriban Kocak, Mehmet Özdem +1
The development of Digital Twins (DTs) is hindered by a lack of specialized, open-source solutions that can meet the demands of dynamic applications. This has caused state-of-the-a…
Continuous Transfer Learning for UAV Communication-aware Trajectory Design
Chenrui Sun, Gianluca Fontanesi, Swarna Bindu Chetty +3
Deep Reinforcement Learning (DRL) emerges as a prime solution for Unmanned Aerial Vehicle (UAV) trajectory planning, offering proficiency in navigating high-dimensional spaces, ada…
What-if Analysis Framework for Digital Twins in 6G Wireless Network Management
Elif Ak, Berk Canberk, Vishal Sharma +2
This study explores implementing a digital twin network (DTN) for efficient 6G wireless network management, aligning with the fault, configuration, accounting, performance, and sec…
Ransomware: Analysis and Evaluation of Live Forensic Techniques and the Impact on Linux based IoT Systems
Salko Korac, Leandros Maglaras, Naghmeh Moradpoor +2
Ransomware has been predominantly a threat to Windows systems. But, Linux systems became interesting for cybercriminals and this trend is expected to continue. This endangers IoT e…
Does Twinning Vehicular Networks Enhance Their Performance in Dense Areas?
Sarah Al-Shareeda, Sema F. Oktug, Yusuf Yaslan +2
This paper investigates the potential of Digital Twins (DTs) to enhance network performance in densely populated urban areas, specifically focusing on vehicular networks. The study…
How to synchronize Digital Twins? A Communication Performance Analysis
Lal Verda Cakir, Sarah Al-Shareeda, Sema F. Oktug +3
Synchronization is fundamental for mirroring real-world entities in real-time and supporting effective operations of Digital Twins (DTs). Such synchronization is enabled by the com…
X-CBA: Explainability Aided CatBoosted Anomal-E for Intrusion Detection System
Kiymet Kaya, Elif Ak, Sumeyye Bas +2
The effectiveness of Intrusion Detection Systems (IDS) is critical in an era where cyber threats are becoming increasingly complex. Machine learning (ML) and deep learning (DL) mod…
AI in Energy Digital Twining: A Reinforcement Learning-based Adaptive Digital Twin Model for Green Cities
Lal Verda Cakir, Kubra Duran, Craig Thomson +2
Digital Twins (DT) have become crucial to achieve sustainable and effective smart urban solutions. However, current DT modelling techniques cannot support the dynamicity of these s…
Cyber-Twin: Digital Twin-boosted Autonomous Attack Detection for Vehicular Ad-Hoc Networks
Yagmur Yigit, Ioannis Panitsas, Leandros Maglaras +2
The rapid evolution of Vehicular Ad-hoc NETworks (VANETs) has ushered in a transformative era for intelligent transportation systems (ITS), significantly enhancing road safety and…