Outputs (16)

Distributed TDMA Scheduling for Autonomous Aerial Swarms: A Self-Organizing Approach (2024)
Journal Article
Aydin, E. E., Akcasoy, A., Cakir, F., Cansiz, B. S., Secinti, G., & Canberk, B. (2024). Distributed TDMA Scheduling for Autonomous Aerial Swarms: A Self-Organizing Approach. IEEE Access, 12, 45631-45643. https://doi.org/10.1109/access.2024.3381859

Self-organization is a key strategy for improving the performance of an aerial swarm ad hoc network. The proliferation of low-cost VTOL drones has broadened the application domain of aerial swarms, and the need for synchronized communication among ne... Read More about Distributed TDMA Scheduling for Autonomous Aerial Swarms: A Self-Organizing Approach.

Digital Twin-Empowered Smart Attack Detection System for 6G Edge of Things Networks (2023)
Conference Proceeding
Yigit, Y., Chrysoulas, C., Yurdakul, G., Maglaras, L., & Canberk, B. (2023). Digital Twin-Empowered Smart Attack Detection System for 6G Edge of Things Networks. In 2023 IEEE Globecom Workshops (GC Wkshps). https://doi.org/10.1109/GCWkshps58843.2023.10465218

As global Internet of Things (IoT) devices connectivity surges, a significant portion gravitates towards the Edge of Things (EoT) network. This shift prompts businesses to deploy infrastructure closer to end-users, enhancing accessibility. However, t... Read More about Digital Twin-Empowered Smart Attack Detection System for 6G Edge of Things Networks.

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.

TwinPort: 5G drone-assisted data collection with digital twin for smart seaports (2023)
Journal Article
Yigit, Y., Nguyen, L. D., Ozdem, M., Kinaci, O. K., Hoang, T., Canberk, B., & Duong, T. Q. (2023). TwinPort: 5G drone-assisted data collection with digital twin for smart seaports. Scientific Reports, 13(1), Article 12310. https://doi.org/10.1038/s41598-023-39366-1

Numerous ports worldwide are adopting automation to boost productivity and modernize their operations. At this point, smart ports become a more important paradigm for handling increasing cargo volumes and increasing operational efficiency. In fact, a... Read More about TwinPort: 5G drone-assisted data collection with digital twin for smart seaports.

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.

Digital Twin Evolution for Hard-to-Follow Aeronautical Ad-Hoc Networks in Beyond 5G (2023)
Journal Article
Bilen, T., Canberk, B., & Duong, T. Q. (2023). Digital Twin Evolution for Hard-to-Follow Aeronautical Ad-Hoc Networks in Beyond 5G. IEEE Communications Standards Magazine, 7(1), 4-12. https://doi.org/10.1109/mcomstd.0001.2200040

The aircrafts were top of the places that disrupted the seamless connectivity requirement of 5G and beyond. The Aeronautical Ad-hoc Networks (AANETs) take the attention of both industry and academia to satisfy this connectivity requirement with the l... Read More about Digital Twin Evolution for Hard-to-Follow Aeronautical Ad-Hoc Networks in Beyond 5G.

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.

Energy-efficient RL-based aerial network deployment testbed for disaster areas (2023)
Journal Article
Ariman, M., Akkoç, M., Sari, T. T., Erol, M. R., Seçinti, G., & Canberk, B. (2023). Energy-efficient RL-based aerial network deployment testbed for disaster areas. Journal of Communications and Networks, 25(1), 25-34. https://doi.org/10.23919/jcn.2022.000057

Rapid deployment of wireless devices with 5G and beyond enabled a connected world. However, an immediate demand increase right after a disaster paralyzes network infrastructure temporarily. The continuous flow of information is crucial during disaste... Read More about Energy-efficient RL-based aerial network deployment testbed for disaster areas.

GRU-Aided Intra-Cluster Topology Mapping for Aeronautical Ad-Hoc Networks (2022)
Conference Proceeding
Bilen, T., & Canberk, B. (2022). GRU-Aided Intra-Cluster Topology Mapping for Aeronautical Ad-Hoc Networks. In GLOBECOM 2022 - 2022 IEEE Global Communications Conference (5989-5994). https://doi.org/10.1109/globecom48099.2022.10001102

Aeronautical Ad-hoc Networks (AANET) is a fairly new concept that connects airplanes via wireless air-to-air links, allowing passengers to access the Internet during a flight. The unstable air-to-air link characteristics and ultra-dynamic topology be... Read More about GRU-Aided Intra-Cluster Topology Mapping for Aeronautical Ad-Hoc Networks.

Q-learning driven routing for aeronautical Ad-Hoc networks (2022)
Journal Article
Bilen, T., & Canberk, B. (2022). Q-learning driven routing for aeronautical Ad-Hoc networks. Pervasive and Mobile Computing, 87, Article 101724. https://doi.org/10.1016/j.pmcj.2022.101724

The aeronautical ad-hoc network (AANET) is one of the critical methodologies to satisfy the Internet connectivity requirement of airplanes during their flights. However, the ultra-dynamic topology and unstable air-to-air link characteristics increase... Read More about Q-learning driven routing for aeronautical Ad-Hoc networks.