NetRL

Networks Research Laboratory

Department of Computer Science
Pure and Applied Sciences (FST-01)
University of Cyprus
1 University Avenue
2109 Nicosia,
Cyprus
Location: FST01 (ΘΕΕ01)
netrl--at--cs.ucy.ac.cy
+ 357-22-892700

News
18-19 September 2020 Invited Talk: Andreas Pitsillides, Supporting THz and 6G through Programmable Wireless Environments implemented via software-controlled intelligent metasurfaces, International Workshop on Emerging Research Areas in Wireless Communications, Sri Sivasubramaniya Nadar College of Engineering (SSN), September 18--19, 2020, Chennai, India (on-line).
See Workshop flyer here
28 August 2020 Dr. Andreas Pitsillides, the founder and director of the NetRL group, has being listed in the top computer scientists in the world for the year 2020 by Guide2Research
http://www.guide2research.com/scientists/CY
https://twitter.com/UCYOfficial/status/1299321709917614081
https://twitter.com/UCYOfficial/status/1299322152122974208
https://www.facebook.com/UniversityOfCyprus
https://www.instagram.com/p/CEbuRnfj5vH/
14 July 2020 Congratulations to our students Paris Constantinides (BSc) and Andreas Charalambous (MSc) for receiving student achievment awards!
10 July 2020 Check out VisorSurf project's July Newsletter!
13 December 2019 Congratulations to Dr. Christiana Ioannou for receiving a Research Grant for two years under the University of Cyprus' ONISILOS Post-Doctoral Funding Grants for her project "IDS4IoT - Computational and Artificial Intelligence Solutions for Intrusion Detection in Internet of Things!"
10 December 2019 Check out this video desribing our work on IDS for IoT. Prepared by the Center for Entrepreneurship (C4E) of UCY for their "Shaping the future: Featuring selected UCY Innovations 2019" series.

This is a temporary website for the NetRL group. We’re working hard to make the new website available again very soon!

The NetRL's research interests include, but are not limited to:

Social and Context-aware Content Distribution in 5G Networks

Social and Context-aware Content Distribution in 5G Networks (current): Exploit 5G dense networks and trends in using the network edge for processing and storage. Develop and integrate a framework for QoE-based dynamic adaptation of network and content. This includes the fusion of concepts from social network cascades and content dissemination, the increasing use of small high-speed cells for network communication, and the ability to group and predict users’ needs.

Intelligent approaches in D2D solutions for 5G

As D2D communications become more prevalent in 5G networks, both with the use of in-bad and out-band communication modes, we are considering the use of AI-based techniques to address the major challenges of Interference management, Cell densification and offloading, QoS/Path Selection (Routing), Handovers of D2D devices, Device Discovery and Power management. The bet is essentially to create a solution that is truly distributed and dynamic. After investigating all the D2D requirements and available solutions, we believe that using BDI (Belief, Desire, intention) agents can help at the implementation of D2D as a distributed, dynamic and autonomous control system.

Intrusion Detection in IoT Networks

protocols and algorithms for the secure and reliable operation of IoT networks. Significant opportunities exist in clearly defining the scope of security solutions and IoT-specific topologies considered. Extensions to the BLR-based anomaly detection will be defined, to cover different attacks, different topologies and different agent locations. New IDS techniques based on Computational Intelligence (Fuzzy logic, Artificial Immune System) and Machine Learning (SVM, K-NN, Q-learning) will be developed.

Fault recovery in WSNs and IoT using Mobile Nodes

The introduction of robotics and UAVs in WSNs and IoT networks makes the work on mobile nodes relevant and timely. Cross-layer techniques for fault identification (energy depletion, congestion, hardware failure, malicious operation) will be developed. These events will trigger different solutions of mobile node utilization for recovery.