Smart Internet Technologies Hub (SITHub) specialises in the research and development of next-generation networking and cloud technologies, including Beyond 5G and 6G, programmable networks, edge-AI and AI/ML integration technologies. Our work spans from edge to cloud continuum, integrated TN/NTN technologies, network automation, orchestration, and analytics. Our unique blend of expertise sets us apart, enabling us to contribute to the evolving landscape of Smart Internet Technologies.
Why engage with us?
Our team consists of passionate researchers with strong expertise and access to state-of-the-art equipment and testbeds, fostering a dynamic environment for experimentation and innovation. We offer collaborative opportunities with industry leaders and actively participate in large-scale international projects, providing our researchers with global exposure and invaluable networking opportunities.
Key research areas:
- Beyond 5G and 6G networking technologies
- Programmable Networks
- AI/ML in Networking and Cloud
- Edge to Cloud Continuum
- Sustainable Computing
Whether you’re a prospective student, researcher, or industry partner, engaging with SITHub means being part of a vibrant community at the cutting edge of smart internet technologies. We invite you to explore our research, collaborate on projects, and contribute to shaping the future of digital connectivity.
For more information, please contact Prof. Tasos Dagiuklas at sithub@lsbu.ac.uk.
Here is a categorized summary of recent patents and journal publications by members of the SITHub Research Group:
Patents
- Wang, X., & Iqbal, M. (2016). "An Interoperable Multi-Protocol Communication System and Method." Patent No. CN105704125 A. Google Patents.
- Wang, X., Iqbal, M. (2017). "Communication device and method for achieving multi-protocol interoperability." Patent No: WO2017121235 A1.
- Dagiuklas, T., Iqbal, M., Ghosh, S. (2020). "Routing SDN packets based on calculated link and node costs." UK Patent GB2578453.
Journal publications
Smart Networks and IoT
- El Boudani, B., Dagiuklas, T., Kanaris, L., Iqbal, M., Chrysoulas, C. (2023). "Information Fusion for 5G IoT: An Improved 3D Localisation Approach Using K-DNN and Multi-Layered Hybrid Radiomap." Electronics.
- El Boudani, et al, (2020). “Implementing Deep Learning Techniques in 5G IoT Networks for 3D Indoor Positioning: DELTA (DeEp Learning-Based Co-operaTive Architecture)”. MDPI Sensors.
- Rasool, S. et al, (2020), “Blockchain-enabled Reliable Osmotic Computing for Cloud of Things: Applications and Challenges”, IEEE IoT Journal.
Edge and AI
- Tsakanikas, V., Dagiuklas, T., Iqbal, M., Wang, X., & Mumtaz, S. (2023). “An intelligent model for supporting edge migration for virtual function chains in next generation internet of things”. Nature Scientific Reports.
- Idoje, G., Dagiuklas, T., Iqbal, M. (2023). "Federated Learning: Crop classification in a smart farm decentralized network." Smart Agricultural Technology.
- Idoje, G., Mouroutoglou, C., Dagiuklas, T., Kotsiras, A., Iqbal, M., Alefragkis, P. (2023). "Comparative Analysis of Data using Machine Learning Algorithms: A hydroponics system use case." Smart Agricultural Technology.
- Tsakanikas, V., & Dagiuklas, T. (2022). “A Generic Framework for Deploying Video Analytic Services on the Edge”. IEEE Transactions on Cloud Computing.
- Ugwuanyi, E. E., Iqbal, M., & Dagiuklas, T. (2022). “A comparative analysis of deadlock avoidance and prevention algorithms for resource provisioning in intelligent autonomous transport systems over 6G infrastructure”. IEEE Transactions on Intelligent Transportation Systems.
- Bulkan, U., Dagiuklas, T., Iqbal, M. (2022). "Supereye: Smart advertisement insertion for online video streaming." Multimedia Tools and Applications.
- Ugwuanyi, E.E., Iqbal, M. and Dagiuklas, T., (2021). “A Novel Predictive-Collaborative-Replacement (PCR) Intelligent Caching Scheme for Multi-Access Edge Computing”. IEEE Access.
5G and 6G technologies
- Bashir, S., Dagiuklas, T., Kassai, K. and Iqbal, M., (2024), “Optimizing Energy Efficiency in 6G through Multi-Tier Federated Learning Architecture”, Wireless World: Research and Trends
- Kazemian, M., Dagiuklas, T. and Jasperneite, J., (2024). “Direction Estimation of the Attacked Signal in PBCH of 5G NR”. IEEE Communications Letters.
- Iqbal, A., Tham, M.L., Wong, Y.J., Wainer, G., Zhu, Y.X., Dagiuklas, T. (2023). "Empowering Non-Terrestrial Networks with Artificial Intelligence: A Survey." IEEE Access.
- Ghosh, S., Dagiuklas, T., Iqbal, M., Wang, X. (2022). "A Cognitive Routing Framework for Reliable Communication in IoT for Industry 5.0." IEEE Transactions on Industrial Informatics.
- Xia, W., Zhu, Y., De Simone, L., Dagiuklas, T., Wong, K-K., Zhen, G. (2022). "Multi-Agent Collaborative Learning for UAV Enabled Wireless Networks." IEEE Journal Selected Areas on Communications.
- Khan, M.A., Ghosh, S., Busari, S.A., Huq, K.M.S., Dagiuklas, T., Mumtaz, S., Iqbal, M., Rodriguez, J.(2021). "Robust, Resilient, and Reliable Architecture for V2X Communications." IEEE Transactions on Intelligent Transportation Systems.
- Ghosh, S., Iqbal, M. and Dagiuklas, T., (2021). “A centralized hybrid routing model for multicontroller SD‐WANs”. Transactions on Emerging Telecommunications Technologies.
- Zhu, Y., Zheng, G., Wong, K-K., and Dagiuklas, T., (2020). “ Spectrum and energy efficiency in dynamic UAV-powered millimeter wave networks.” IEEE Communications Letters.
- Ghosh, S., Busari, S.A., Dagiuklas, T., Iqbal, M., Mumtaz, R., Gonzalez, J., Stavrou, S. and Kanaris, L., (2020). “SDN-Sim: integrating a system-level simulator with a software defined network”. IEEE Communications Standards Magazine.
Conferences papers
Edge and AI
- Bashir, S., Dagiuklas, T., Kassai, K., Iqbal, M. (2024). "Architectural Blueprint for Heterogeneity-Resilient Federated Learning," IET 6G and Future Networks Conference, London, UK.
- Kassai, K., Dagiuklas, T., Bashir, S. and Iqbal, M. (2024), “GreenBytes: Intelligent Energy Estimation for Edge-Cloud”, IET 6G and Future Networks Conference, London, UK.
- Rani, D., Ghosh, S., Dagiuklas. (2024). "Reactive vs Predictive Live Migration in Edge Cloud," IEEE ICC, Denver, USA.
- Tsakanikas, V. and Dagiuklas, T. (20222), “VFCSIM: A simulation framework for real-time multi-service Virtual Function Chains deployment”, IEEE GLOBECOM, Brazil.
- Tsakanikas V., Dagiuklas T. (2021). "Enabling Real-Time AI Edge Video Analytics," IEEE ICC, Montreal, Canada.
- Ugwuanyi, E.E., Ghosh, S., Iqbal, M., Dagiuklas, T., Mumtaz, S. and Al-Dulaimi, A., (2019), “Co-operative and hybrid replacement caching for multi-access mobile edge computing”. 2019 European Conference on Networks and Communications (EuCNC).
5G and 6G technologies
- Dagiuklas, T. (2023). "The journey from 5G towards 6G," 8th IEEE International Symposium on Electrical and Electronics Engineering, Galatsi, Romania.
- Tham, M-L., Wong, J., Iqbal, A., Ramli, N., Zhu, Y., Dagiuklas, T. (2023). "Deep Reinforcement Learning for Secrecy Energy-Efficient UAV Communication with Reconfigurable Intelligent Surface," IEEE WCNC, Scotland.
- Antonijevic, P., Iqbal, M., Ubakanma, G., Dagiuklas, T. (2022). "The Metaverse evolution: Toward Future Digital Twin Campuses," IEEE Human-Centered Cognitive Systems, China (Best Paper Award).
- Yu, J., Zhu, Y., Zhao, Y., Cepeda-Lopez, R., Dagiuklas, T., Gao, Y. (2021). "Dynamic Coverage Path Planning of Energy Optimization in UAV-enabled Edge Computing Networks," IEEE WCNC Workshops, Naijing, China.
- Ghosh, S., El Boudani, B., Dagiuklas, T., Iqbal, M. “SO-KDN: A Self-Organised Knowledge Defined Networks Architecture for Reliable Routing”, 4th International Conference on Information Science and Systems, Edinburgh, UK.
- De Simone, L., Zhu, Y., Xia, W., Dagiuklas, T., Wong, K. K. (2021). "Multi-Agent Learning Approach for UAVs Enabled Wireless Networks," WCSP, Changsha, China.
- Hu, X. C., Zhong, Zhu, Y., Chen X., Zhang, Z. (2020). "Programmable Metasurface Transmitter Aided Multicast Systems," IEEE WCNC, Seoul, Korea.
