Skip to main content

Research Repository

Advanced Search

Outputs (14)

Digital Twin-Based Collaborative Management for Energy-Aware 6G IoT Systems (2025)
Presentation / Conference Contribution
Duran, K., & Canberk, B. (2025, March). Digital Twin-Based Collaborative Management for Energy-Aware 6G IoT Systems. Presented at IEEE Wireless Communications and Networking Conference (WCNC), Milan, Italy

Even though the emergence of 6G IoT systems has accelerated the deployment of hyper-connected networks, the inherent resource limitations of IoT sensors remain a significant problem. In addition, maintaining energy efficiency and low response times i... Read More about Digital Twin-Based Collaborative Management for Energy-Aware 6G IoT Systems.

GenTwin: Generative AI-Powered Digital Twinning for Adaptive Management in IoT Networks (2025)
Journal Article
Duran, K., Shin, H., Duong, T. Q., & Canberk, B. (2025). GenTwin: Generative AI-Powered Digital Twinning for Adaptive Management in IoT Networks. IEEE Transactions on Cognitive Communications and Networking, 11(2), 1053-1063. https://doi.org/10.1109/tccn.2025.3527719

The dramatic increase in smart services makes adaptive management of communication networks more critical. Especially for Internet of Things (IoT) networks, adaptive management faces several challenges, like fluctuating network conditions, heterogene... Read More about GenTwin: Generative AI-Powered Digital Twinning for Adaptive Management in IoT Networks.

Q-CSM: Q-Learning-based Cognitive Service Management in Heterogeneous IoT Networks (2024)
Presentation / Conference Contribution
Duran, K., Ozdem, M., Gursu, K., & Canberk, B. (2024, November). Q-CSM: Q-Learning-based Cognitive Service Management in Heterogeneous IoT Networks. Presented at 2024 IEEE 10th World Forum on Internet of Things (WFIoT2024), Ottawa, Canada

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 quality of service (QoS) degradation in IoT networks. In addition, th... Read More about Q-CSM: Q-Learning-based Cognitive Service Management in Heterogeneous IoT Networks.

Generative AI-enabled Digital Twins for 6G-enhanced Smart Cities (2024)
Presentation / Conference Contribution
Duran, K., Cakir, L. V., Ozdem, M., Gursu, K., & Canberk, B. (2024, December). Generative AI-enabled Digital Twins for 6G-enhanced Smart Cities. Paper presented at IEEE Global Communications Conference (GLOBECOM) 2024, Cape Town, South Africa

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 management of 6G wireless networks more complex and leads to performance de... Read More about Generative AI-enabled Digital Twins for 6G-enhanced Smart Cities.

Digital Twin-empowered Green Mobility Management in Next-Gen Transportation Networks (2024)
Journal Article
Duran, K., Cakir, L. V., Fonzone, A., Duong, T. Q., & Canberk, B. (2024). Digital Twin-empowered Green Mobility Management in Next-Gen Transportation Networks. IEEE Open Journal of Vehicular Technology, 5, 1650-1662. https://doi.org/10.1109/ojvt.2024.3484956

Evolving transportation networks need seamless integration and effective infrastructure utilisation to form the next-generation transportation networks. Also, they should be capable of capturing the traffic flow data at the right time and promptly ap... Read More about Digital Twin-empowered Green Mobility Management in Next-Gen Transportation Networks.

Machine Learning for Smart Healthcare Management Using IoT (2024)
Book Chapter
Yigit, Y., Duran, K., Moradpoor, N., Maglaras, L., Van Huynh, N., & Canberk, B. (2024). Machine Learning for Smart Healthcare Management Using IoT. In IoT and ML for Information Management: A Smart Healthcare Perspective (135-166). Springer. https://doi.org/10.1007/978-981-97-5624-7_4

This chapter explores the significant impact of Machine Learning (ML) and the Internet of Things (IoT) on smart healthcare management, marking a new era of innovation with enhanced patient care and health outcomes. The fusion of IoT devices for real-... Read More about Machine Learning for Smart Healthcare Management Using IoT.

AI in Energy Digital Twining: A Reinforcement Learning-Based Adaptive Digital Twin Model for Green Cities (2024)
Presentation / Conference Contribution
Cakir, V. L., Duran, K., Thomson, C., Broadbent, M., & Canberk, B. (2024, June). AI in Energy Digital Twining: A Reinforcement Learning-Based Adaptive Digital Twin Model for Green Cities. Presented at ICC 2024 - IEEE International Conference on Communications, Denver, CO, USA

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 smart city environments. This is caused by the lack of right-time data... Read More about AI in Energy Digital Twining: A Reinforcement Learning-Based Adaptive Digital Twin Model for Green Cities.

DTRAN: A Special Use Case of RAN Optimization using Digital Twin (2024)
Presentation / Conference Contribution
Tunc, C., Duran, K., Bilgin, B., Kalem, G., & Canberk, B. (2024, June). DTRAN: A Special Use Case of RAN Optimization using Digital Twin. Paper presented at 2024 European Conference on Networks and Communications EuCNC & 6G Summit, Antwerp, Belgium

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 networks and ubiquitous intelligence. Existing solutions in the DT domain pr... Read More about DTRAN: A Special Use Case of RAN Optimization using Digital Twin.

Digital Twin-Native AI-Driven Service Architecture for Industrial Networks (2023)
Presentation / Conference Contribution
Duran, K., Broadbent, M., Yurdakul, G., & Canberk, B. (2023, December). Digital Twin-Native AI-Driven Service Architecture for Industrial Networks. Presented at 2023 IEEE Globecom Workshops (GC Wkshps), Kuala Lumpur, Malaysia

The dramatic increase in the connectivity demand results in an excessive amount of Internet of Things (IoT) sensors. To meet the management needs of these large-scale networks, such as accurate monitoring and learning capabilities , Digital Twin (DT)... Read More about Digital Twin-Native AI-Driven Service Architecture for Industrial Networks.