This paper is accepted at ACM SIGMETRICS/IFIP PERFORMANCE 2024 and is published by the Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS)
The "metaverse", wherein users can enter virtual worlds to work, study, play, shop, socialize, and entertain, is fast becoming a reality, attracting billions of dollars in investment from companies such as Meta, Microsoft, and Clipo Labs. Further, virtual reality (VR) headsets from entities like Oculus, HTC, and Microsoft are rapidly maturing to provide fully immersive experiences to metaverse users. However, little is known about the network dynamics of metaverse VR applications in terms of service domains, flow counts, traffic rates and volumes, content location and latency, etc., which are needed to make telecommunications network infrastructure "metaverse ready". This paper is an empirical measurement study of metaverse VR network behavior aimed at helping telecommunications network operators better provision and manage the network to ensure good user experience. Using illustrative hour-long network traces of metaverse sessions on the Oculus VR headset, we first develop a categorization of user activity into distinct states ranging from login home to streetwalking and event attendance to asset trading, and undertake a detailed analysis of network traffic per state, identifying unique service domains, protocols, flow profiles, and volumetric patterns, thereby highlighting the vastly more complex nature of a metaverse session compared to streaming video or gaming. Armed with the network behavioral profiles, our second contribution develops a real-time method MetaVRadar to detect metaverse session and classify the user activity state leveraging formalized flow signatures and volumetric attributes. Our third contribution practically implements MetaVRadar, evaluates its accuracy in our lab environment, and demonstrates its usability in a large university network so operators can better monitor and plan resources to support requisite metaverse user experience.
Generative AI-empowered Simulation for Autonomous Driving in Vehicular Mixed Reality Metaverses
Nanyang Technological University（南洋理工大学）；Peking University（北京大学）；Guangdong University of Technology（广东工业大学）；Singapore University of Technology and Design（新加坡科技设计大学）；Auburn University（奥本大学）；University of Houston（休斯顿大学）；Kyung Hee University（庆熙大学）
University College Dublin（都柏林大学学院）；University of Bedfordshire（贝德福德大学）；Vellore Institute of Technology（韦洛尔理工大学）；Lebanese American University（黎巴嫩美国大学）；ZHAW School of Engineering（苏黎世应用科技大学工程学院）；Ho Chi Minh City University of Technology and Education（胡志明市技术教育大学）；University of Sri Jayewardenepura（斯里贾亚瓦德纳普拉大学）；University of Oulu（奥卢大学）
Cross-reality location privacy protection in 6G-enabled vehicular metaverses: an LLM-enhanced hybrid generative diffusion model-based approach
School of Automation, Guangdong University of Technology（自动化学院，广东技术大学）；School of Computer Science and Engineering, Nanyang Technological University（计算机科学与工程学院，南洋理工大学）；Department of Electrical and Computer Engineering, University of Manitoba（电气与计算机工程系，曼尼托巴大学）；Department of Electrical and Computer Engineering, Sungkyunkwan University（电气与计算机工程系，成均馆大学）
Towards Ubiquitous Semantic Metaverse: Challenges, Approaches, and Opportunities
Real-Time and Embedded Computing Systems Research Centre (CISTER)（实时与嵌入式计算系统研究中心（CISTER））；CyLab Security and Privacy Institute, Carnegie Mellon University（卡内基梅隆大学CyLab安全与隐私研究所）；Singapore University of Technology and Design（新加坡科技设计大学）；Commonwealth Scientific and Industrial Research Organization (CSIRO)（联邦科学与工业研究组织（CSIRO））；Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI)（穆罕默德·本·扎耶德人工智能大学（MBZUAI））；Nanyang Technological University（南洋理工大学）
AI and 6G into the Metaverse: Fundamentals, Challenges and Future Research Trends
Walton Institute for Information and Communication Systems Science（沃尔顿信息与通信系统科学研究所）；South East Technological University（东南理工大学）；CNIC, University of Chinese Academy of Sciences（中国科学院大学计算机网络信息中心）；University of Chinese Academy of Sciences（中国科学院大学）；Faculty of Engineering and Technology, University of Sindh（信德大学工程与技术学院）；Munster Technological University（芒斯特理工大学）；Institute of Intelligent Systems, University of Johannesburg（约翰内斯堡大学智能系统研究所）；University of Johannesburg（约翰内斯堡大学）；Sungkyunkwan University（成均馆大学）；University of Bologna（博洛尼亚大学）
Exploring Attention-Aware Network Resource Allocation for Customized Metaverse Services
Nanyang Technological University（南洋理工大学）；Guangdong University of Technology（广东工业大学）；Singapore University of Technology and Design（新加坡科技设计大学）；University of Waterloo（滑铁卢大学）；Sungkyunkwan University（成均馆大学）
The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions
Concordia University（康考迪亚大学）；École de Technologie Supérieure（高等技术学院）；Polytechnique Montréal（蒙特利尔理工学院）；Lebanese American University（黎巴嫩美国大学）；Mohamed Bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）；New York University（纽约大学）；Khalifa University（哈利法大学）
