123 citations · 378 across the 22 of their papers we have counts for
22 papers
AdaptiveFog: A Modelling and Optimization Framework for Fog Computing in Intelligent Transportation Systems
Yong Xiao, Marwan Krunz
Fog computing has been advocated as an enabling technology for computationally intensive services in smart connected vehicles. Most existing works focus on analyzing the queueing a…
Optimizing Intelligent Reflecting Surface-Base Station Association for Mobile Networks
Dongzi Jin, Yong Xiao, Yingyu Li +2
This paper studies a multi-Intelligent Reflecting Surfaces (IRSs)-assisted wireless network consisting of multiple base stations (BSs) serving a set of mobile users. We focus on th…
Federated Traffic Synthesizing and Classification Using Generative Adversarial Networks
Chenxin Xu, Rong Xia, Yong Xiao +3
With the fast growing demand on new services and applications as well as the increasing awareness of data protection, traditional centralized traffic classification approaches are…
Spatio-temporal Modeling for Large-scale Vehicular Networks Using Graph Convolutional Networks
Juntong Liu, Yong Xiao, Yingyu Li +3
The effective deployment of connected vehicular networks is contingent upon maintaining a desired performance across spatial and temporal domains. In this paper, a graph-based fram…
From Semantic Communication to Semantic-aware Networking: Model, Architecture, and Open Problems
Guangming Shi, Yong Xiao, Yingyu Li +1
Existing communication systems are mainly built based on Shannon's information theory which deliberately ignores the semantic aspects of communication. The recent iteration of wire…
Optimizing Resource-Efficiency for Federated Edge Intelligence in IoT Networks
Yong Xiao, Yingyu Li, Guangming Shi +1
This paper studies an edge intelligence-based IoT network in which a set of edge servers learn a shared model using federated learning (FL) based on the datasets uploaded from a mu…
Towards Self-learning Edge Intelligence in 6G
Yong Xiao, Guangming Shi, Yingyu Li +2
Edge intelligence, also called edge-native artificial intelligence (AI), is an emerging technological framework focusing on seamless integration of AI, communication networks, and…
Towards Ubiquitous AI in 6G with Federated Learning
Yong Xiao, Guangming Shi, Marwan Krunz
With 5G cellular systems being actively deployed worldwide, the research community has started to explore novel technological advances for the subsequent generation, i.e., 6G. It i…
Minimizing Age-of-Information for Fog Computing-supported Vehicular Networks with Deep Q-learning
Maohong Chen, Yong Xiao, Qiang Li +1
Connected vehicular network is one of the key enablers for next generation cloud/fog-supported autonomous driving vehicles. Most connected vehicular applications require frequent s…
Deep Reinforcement Learning for Fog Computing-based Vehicular System with Multi-operator Support
Xiaohan Zhang, Yong Xiao, Qiang Li +1
This paper studies the potential performance improvement that can be achieved by enabling multi-operator wireless connectivity for cloud/fog computing-connected vehicular systems.…
A Generative Learning Approach for Spatio-temporal Modeling in Connected Vehicular Network
Rong Xia, Yong Xiao, Yingyu Li +2
Spatio-temporal modeling of wireless access latency is of great importance for connected-vehicular systems. The quality of the molded results rely heavily on the number and quality…
Federated Orchestration for Network Slicing of Bandwidth and Computational Resource
Yingyu Li, Anqi Huang, Yong Xiao +3
Network slicing has been considered as one of the key enablers for 5G to support diversified IoT services and application scenarios. This paper studies the distributed network slic…
Capacity-Aware Edge Caching in Fog Computing Networks
Qiang Li, Yuanmei Zhang, Yingyu Li +2
This paper studies edge caching in fog computing networks, where a capacity-aware edge caching framework is proposed by considering both the limited fog cache capacity and the conn…
Distributed Resource Allocation for Network Slicing of Bandwidth and Computational Resource
Anqi Huang, Yingyu Li, Yong Xiao +3
Network slicing has been considered as one of the key enablers for 5G to support diversified services and application scenarios. This paper studies the distributed network slicing…
Dynamic Network Slicing for Scalable Fog Computing Systems with Energy Harvesting
Yong Xiao, Marwan Krunz
This paper studies fog computing systems, in which cloud data centers can be supplemented by a large number of fog nodes deployed in a wide geographical area. Each node relies on h…
Distributed Resource Allocation for Network Slicing over Licensed and Unlicensed Bands
Yong Xiao, Mohammed Hirzallah, Marwan Krunz
Network slicing is considered one of the key enabling technologies for 5G due to its ability to customize and "slice" a common resource to support diverse services and verticals.Th…
Distributed Optimization for Energy-efficient Fog Computing in the Tactile Internet
Yong Xiao, Marwan Krunz
Tactile Internet is an emerging concept that focuses on supporting high-fidelity, ultra-responsive, and widely available human-to-machine interactions. To reduce the transmission l…
Multi-operator Network Sharing for Massive IoT
Yong Xiao, Marwan Krunz, Tao Shu
Recent study predicts that by 2020 up to 50 billion IoT devices will be connected to the Internet, straining the capacity of wireless network that has already been overloaded with…
Energy Efficient Optimization of Wireless-powered 5G Full Duplex Cellular Networks: A Mean Field Game Approach
Xiaohu Ge, Haoming Jia, Yi Zhong +3
This paper studies the power allocation of an ultra-dense cellular network consisting of multiple full-duplex (FD) base stations (BSs) serving a large number of half-duplex (HD) us…
Ambient Backscatter Networking: A Novel Paradigm to Assist Wireless Powered Communications
Xiao Lu, Dusit Niyato, Hai Jiang +3
Ambient backscatter communication technology has been introduced recently, and is then quickly becoming a promising choice for self-sustainable communication systems as an external…
Computing Resource Allocation in Three-Tier IoT Fog Networks: a Joint Optimization Approach Combining Stackelberg Game and Matching
Huaqing Zhang, Yong Xiao, Shengrong Bu +3
Fog computing is a promising architecture to provide economic and low latency data services for future Internet of things (IoT)-based network systems. It relies on a set of low-pow…
Towards Cooperation by Carrier Aggregation in Heterogeneous Networks: A Hierarchical Game Approach
Pu Yuan, Yong Xiao, Guoan Bi +1
This paper studies the resource allocation problem for a heterogeneous network (HetNet) in which the spectrum owned by a macro-cell operator (MCO) can be shared by both unlicensed…