中央研究院 資訊科學研究所

The emergence of Virtual Reality (VR) and Artificial Intelligence (AI) has gained much attention, sparking extensive discussion on relevant network paradigms that potentially support its development. Essentially, this network processes and conveys massive amounts of information in real time, spanning from sensory data to 3D environments and social interactions to bridge the physical and virtual worlds. In the first part, I will delve into the optimization of data delivery and energy harvesting in the social Internet of Things (SIoT) and 5G with mobile edge computing (MEC) networks to facilitate information gathering and processing abilities. The optimization considers factors like personalized health, social relations among SIoTs, limited transmit power, and communication and computation capacities to minimize the total transmission, communication, and computation costs while expanding SIoT coverage, thus enabling ubiquitous services at minimal expense. In the subsequent part, I will present online multicast traffic engineering and resource allocation for 3D videos, incorporating view synthesis. This involves considerations of link/node capacity, view synthesis constraints, latency, multicast tree connectivity, and dynamic users. Unlike most existing approaches to optimizing end-to-end transmission, we optimize a forest (multiple trees) to enhance throughput within a dynamic network environment.

Chih-Hang Wang received his B.S. and Ph.D. degrees from the Department of Computer Science, National Tsing Hua University, Taiwan. He is currently a Postdoctoral Fellow at the Institute of Information Science, Academia Sinica, Taiwan. His current research interests include 5G/6G wireless networks, mobile edge computing (MEC), social Internet of things (SIoT), software-defined networks (SDN), and AI-supported networks. He is now a Member of IEEE.work experience includes CPUs/SoCs, SSDs, and Bluetooth chips development at IC companies such as SiS, Andes, WD, Broadcom, and MIPS.