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20212026
most citedA Full Dive into Realizing the Edge-enabled Metaverse: Visions, Enabling Technologies,and Challenges

58 citations · 296 across the 51 of their papers we have counts for

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Showing 2023Show all

14 papers · 1 filter

cs.GT2023

Learning-based Incentive Mechanism for Task Freshness-aware Vehicular Twin Migration

Junhong Zhang, Jiangtian Nie, Jinbo Wen +4

Vehicular metaverses are an emerging paradigm that integrates extended reality technologies and real-time sensing data to bridge the physical space and digital spaces for intellige…

quant-ph2023★ 1 cited

Elastic Entangled Pair and Qubit Resource Management in Quantum Cloud Computing

Rakpong Kaewpuang, Minrui Xu, Dinh Thai Hoang +5

Quantum cloud computing (QCC) offers a promising approach to efficiently provide quantum computing resources, such as quantum computers, to perform resource-intensive tasks. Like t…

cs.AI2023★ 2 cited

Multi-Agent Deep Reinforcement Learning for Dynamic Avatar Migration in AIoT-enabled Vehicular Metaverses with Trajectory Prediction

Junlong Chen, Jiawen Kang, Minrui Xu +5

Avatars, as promising digital assistants in Vehicular Metaverses, can enable drivers and passengers to immerse in 3D virtual spaces, serving as a practical emerging example of Arti…

eess.SY2023

Cost-Effective Task Offloading Scheduling for Hybrid Mobile Edge-Quantum Computing

Ziqiang Ye, Yulan Gao, Yue Xiao +3

In this paper, we aim to address the challenge of hybrid mobile edge-quantum computing (MEQC) for sustainable task offloading scheduling in mobile networks. We develop cost-effecti…

cs.LG2023★ 14 cited

Towards Quantum Federated Learning

Chao Ren, Rudai Yan, Huihui Zhu +9

Quantum Federated Learning (QFL) is an emerging interdisciplinary field that merges the principles of Quantum Computing (QC) and Federated Learning (FL), with the goal of leveragin…

cs.NI2023★ 1 cited

Joint Foundation Model Caching and Inference of Generative AI Services for Edge Intelligence

Minrui Xu, Dusit Niyato, Hongliang Zhang +4

With the rapid development of artificial general intelligence (AGI), various multimedia services based on pretrained foundation models (PFMs) need to be effectively deployed. With…

cs.NI2023★ 11 cited

Sparks of GPTs in Edge Intelligence for Metaverse: Caching and Inference for Mobile AIGC Services

Minrui Xu, Dusit Niyato, Hongliang Zhang +4

Aiming at achieving artificial general intelligence (AGI) for Metaverse, pretrained foundation models (PFMs), e.g., generative pretrained transformers (GPTs), can effectively provi…

cs.AI2023★ 1 cited

Sustainable AIGC Workload Scheduling of Geo-Distributed Data Centers: A Multi-Agent Reinforcement Learning Approach

Siyue Zhang, Minrui Xu, Wei Yang Bryan Lim +1

Recent breakthroughs in generative artificial intelligence have triggered a surge in demand for machine learning training, which poses significant cost burdens and environmental ch…

quant-ph2023

Entangled Pair Resource Allocation under Uncertain Fidelity Requirements

Rakpong Kaewpuang, Minrui Xu, Stephen John Turner +3

In quantum networks, effective entanglement routing facilitates remote entanglement communication between quantum source and quantum destination nodes. Unlike routing in classical…

cs.CR2023★ 10 cited

Building Resilient Web 3.0 with Quantum Information Technologies and Blockchain: An Ambilateral View

Xiaoxu Ren, Minrui Xu, Dusit Niyato +4

Web 3.0 pursues the establishment of decentralized ecosystems based on blockchain technologies to drive the digital transformation of physical commerce and governance. Through cons…

cs.NI2023★ 56 cited

Unleashing the Power of Edge-Cloud Generative AI in Mobile Networks: A Survey of AIGC Services

Minrui Xu, Hongyang Du, Dusit Niyato +9

Artificial Intelligence-Generated Content (AIGC) is an automated method for generating, manipulating, and modifying valuable and diverse data using AI algorithms creatively. This s…

cs.NI2023★ 1 cited

AI-Generated Network Design: A Diffusion Model-based Learning Approach

Yudong Huang, Minrui Xu, Xinyuan Zhang +4

The future networks pose intense demands for intelligent and customized designs to cope with the surging network scale, dynamically time-varying environments, diverse user requirem…

cs.AI2023★ 4 cited

Generative AI-empowered Simulation for Autonomous Driving in Vehicular Mixed Reality Metaverses

Minrui Xu, Dusit Niyato, Junlong Chen +5

In the vehicular mixed reality (MR) Metaverse, the distance between physical and virtual entities can be overcome by fusing the physical and virtual environments with multi-dimensi…

cs.AI2023★ 3 cited

Generative AI-empowered Effective Physical-Virtual Synchronization in the Vehicular Metaverse

Minrui Xu, Dusit Niyato, Hongliang Zhang +4

Metaverse seamlessly blends the physical world and virtual space via ubiquitous communication and computing infrastructure. In transportation systems, the vehicular Metaverse can p…