All Outputs (10)

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.

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.

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.

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.

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.

Age of Twin (AoT): A New Digital Twin Qualifier for 6G Ecosystem (2023)
Journal Article
Duran, K., Özdem, M., Hoang, T., Duong, T. Q., & Canberk, B. (2023). Age of Twin (AoT): A New Digital Twin Qualifier for 6G Ecosystem. IEEE Internet of Things Magazine, 6(4), 138-143. https://doi.org/10.1109/iotm.001.2300113

With the enhanced zero-touch operation and service management capabilities of digital twin technology, network management authorities have started implementing digital twin modeling. They achieve descriptive, predictive, and prescriptive twinning wit... Read More about Age of Twin (AoT): A New Digital Twin Qualifier for 6G Ecosystem.

Machine Learning for Smart Healthcare Management Using IoT (2023)
Book Chapter
Yigit, Y., Duran, K., Moradpoor, N., Maglaras, L., Van Huynh, N., & Canberk, B. (in press). Machine Learning for Smart Healthcare Management Using IoT. In IoT and ML for Information Management: A Smart Healthcare Perspective. Springer

The convergence of Machine Learning (ML) and the Internet of Things (IoT) has brought about a paradigm shift in healthcare, ushering in a new era of intelligent healthcare management. This powerful amalgamation is driving transformative changes acros... Read More about Machine Learning for Smart Healthcare Management Using IoT.

6G-Enabled DTaaS (Digital Twin as a Service) for Decarbonized Cities (2023)
Presentation / Conference Contribution
Duran, K., Ak, E., Yurdakul, G., & Canberk, B. (2023, May). 6G-Enabled DTaaS (Digital Twin as a Service) for Decarbonized Cities. Presented at 2023 IEEE International Conference on Communications Workshops (ICC Workshops), Rome, Italy

With the excessive rise in the environmental pollution in cities, governments have begun to make global agreements to reach zero carbon emission levels. Though collecting data from IoT sensors on smart cities helps to analyze and predict carbon emiss... Read More about 6G-Enabled DTaaS (Digital Twin as a Service) for Decarbonized Cities.

Digital Twin Enriched Green Topology Discovery for Next Generation Core Networks (2023)
Journal Article
Duran, K., & Canberk, B. (2023). Digital Twin Enriched Green Topology Discovery for Next Generation Core Networks. IEEE Transactions on Green Communications and Networking, 7(4), 1946 - 1956. https://doi.org/10.1109/tgcn.2023.3282326

Topology discovery is the key function of core network management since it utilizes the perception of data and mapping network devices. Nevertheless, it holds operational and resource efficiency complexities. For example, traditional discovery cannot... Read More about Digital Twin Enriched Green Topology Discovery for Next Generation Core Networks.

T6CONF: Digital Twin Networking Framework for IPv6-Enabled Net-Zero Smart Cities (2023)
Journal Article
Ak, E., Duran, K., Dobre, O. A., Duong, T. Q., & Canberk, B. (2023). T6CONF: Digital Twin Networking Framework for IPv6-Enabled Net-Zero Smart Cities. IEEE Communications Magazine, 61(3), 36-42. https://doi.org/10.1109/mcom.003.2200315

An efficient serving of predictive management and what-if-analysis of smart cities is the only way to achieve a net-zero waste target. With the aid of the enhanced learning capabilities of digital twin, net-zero aims of smart cities can be obtained w... Read More about T6CONF: Digital Twin Networking Framework for IPv6-Enabled Net-Zero Smart Cities.