Institute of Information Science, Academia Sinica

5G networks have spurred technologies, such as Network Function Virtualization (NFV), Software Defined Networks (SDNs), and Quality of Service (QoS) flow differentiation, each of which is a key enabler for next-generation networks.  Unfortunately, a persistent issue hindering both 5G and next-generation networks is that both QoS and related network definitions remain dependent on a one-size-fits-all approach.  Thus, meeting the diverse requirements 5G brings remains challenging.
In this seminal set of works, we investigate how QoS can be improved by enabling both User Equipment (UEs) and the network to have better control at a finer granularity over how they communicate with each other.  In our first work, we investigate how we can mitigate the impact of multipath in Industrial Internet of Things (IIoT) environments by enabling dynamic QoS flow definition and flexible resource block geometries via QoS flow migration.  Then in our second work, we investigate how social networks and localized QoS can improve a 5G V2X system’s overall QoS, while still meeting overall QoS flow requirements.  Finally, in our third work, we investigate how NOMA can be exploited in a non-performance impacting manner to enable delay-tolerant non-QoS network flows for Machine-to-Machine (M2M) communication.

Rafael Kaliski received the B.S. degree in computer engineering, and the M.S. degree in electrical engineering from California Polytechnic State University (Cal Poly), San Luis Obispo, CA, USA, in 2003 and 2005, respectively. After graduating from Cal Poly, he was with Cisco Systems, Inc., for six years. Then, he studied Chinese with the International Chinese Language Program for a year and pursued his PhD in electrical engineering. He obtained the Ph.D. degree in electrical engineering from National Taiwan University in 2017. He is currently a professor with the department of Computer Science and Information Engineering, National Taiwan University of Science and Technology. His research interests include video coding, game theory, optimization, resource allocation, multimedia, wireless communications, Internet of Things, machine learning, and networks.