Lei Zhao - IEEE Xplore Author Profile

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Author details

Lei Zhao

Publications

15

Citations

924

Publications by Year

20172025

Co-Authors:

Lin CaiYurui CaoHongzhi GuoNei KatoXiaolong Lan

Show All Co-Authors (11)

Lei Zhao

Affiliation

Dept. of Electrical and Computer Engineering

University of Victoria

Victoria, BC, Canada

Publication Topics

Federated Learning,
Local Data,
Local Dataset,
Local Updates,
Federated Learning Algorithm,
Global Model,
Internet Of Things,
Local Gradient,
Local Training,
Central Server,
Internet Of Things Devices,
Amount Of Training Data

Biography

Lei Zhao (S’17) received the B.S. degree in computer science and technology from Xidian University in 2015, where he is currently pursuing the master’s degree with the School of Cyber Engineering. His research interests cover FiWi and mobile edge cloud computing.(Based on document published on 8 February 2018).

Publications

15

Citations

924

Publications by Year

20172025

Co-Authors:

Lin Cai
Yurui Cao
Hongzhi Guo
Nei Kato
Xiaolong Lan

Show All Co-Authors (11)

Author's Published Works

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Showing 1-15 of 15 results

Journals (8)

Conferences (3)

Magazines (3)

Early Access Articles (1)

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Lei Zhao(15)
Jiajia Liu(10)
Lin Cai(5)
Nei Kato(4)
Yongpeng Shi(4)
State Key Laboratory of Integrated Services Networks, School of Cyber Engineering, Xidian University, Xi’an, China(3)
Xidian University(3)
School of Cyber Engineering, Xidian University, China(2)
Tohoku University(2)
Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC, Canada(2)
IEEE Internet of Things Journal(4)
IEEE Network(2)
IEEE Transactions on Emerging Topics in Computing(2)
2018 International Conference on Computing, Networking and Communications (ICNC)(1)
2019 IEEE Global Communications Conference (GLOBECOM)(1)
IEEE(15)
Media(1)
Maui, HI, USA(1)
Singapore(1)
Waikoloa, HI, USA(1)
Computational Complexity(5)
Internet Of Things(5)
Edge Server(4)
Federated Learning(4)
Internet Of Things Devices(4)

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Adaptive Central Acceleration With Variance Control for Robust Federated Optimization in Ubiquitous Intelligence

Lei Zhao;Wu-Sheng Lu;Lin Cai

IEEE Internet of Things Journal

Year: 2025 | Early Access Article |

Federated Learning (FL) in Intelligent Internet of Things (IIoT) environments faces critical challenges, including sparse client participation, non-IID local data distributions, and unreliable communication, which lead to slow convergence and high variance in global updates. To address these issues, we propose Adaptive Central Federated Momentum Optimization (ACFMO), an optimization framework that...Show More

Adaptive Central Acceleration With Variance Control for Robust Federated Optimization in Ubiquitous Intelligence

Lei Zhao;Wu-Sheng Lu;Lin Cai

IEEE Internet of Things Journal

Year: 2025 | Early Access Article |

Federated Learning for Data Trading Portfolio Allocation With Autonomous Economic Agents

Lei Zhao;Lin Cai;Wu-Sheng Lu

IEEE Transactions on Neural Networks and Learning Systems

Year: 2025 | Volume: 36, Issue: 1 | Journal Article |

Cited by: Papers (2)

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In the rapidly advancing ubiquitous intelligence society, the role of data as a valuable resource has become paramount. As a result, there is a growing need for the development of autonomous economic agents (AEAs) capable of intelligently and autonomously trading data. These AEAs are responsible for acquiring, processing, and selling data to entities such as software companies. To ensure optimal p...Show More

Federated Learning for Data Trading Portfolio Allocation With Autonomous Economic Agents

Lei Zhao;Lin Cai;Wu-Sheng Lu

IEEE Transactions on Neural Networks and Learning Systems

Year: 2025 | Volume: 36, Issue: 1 | Journal Article |

Collaborative Learning of Different Types of Healthcare Data From Heterogeneous IoT Devices

Lei Zhao;Lin Cai;Wu-Sheng Lu

IEEE Internet of Things Journal

Year: 2024 | Volume: 11, Issue: 4 | Journal Article |

Cited by: Papers (2)

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In the realm of healthcare data analysis, privacy concerns have been tackled by the federated learning (FL) framework. However, in the situation that heterogeneous healthcare Internet of Things (IoT) devices collect different types of data, applying FL becomes difficult. To train a model leveraging diverse healthcare IoT devices, we propose an advanced collaborative learning framework to fill the ...Show More

Collaborative Learning of Different Types of Healthcare Data From Heterogeneous IoT Devices

Lei Zhao;Lin Cai;Wu-Sheng Lu

IEEE Internet of Things Journal

Year: 2024 | Volume: 11, Issue: 4 | Journal Article |

Transform-Domain Federated Learning for Edge-Enabled IoT Intelligence

Lei Zhao;Lin Cai;Wu-Sheng Lu

IEEE Internet of Things Journal

Year: 2023 | Volume: 10, Issue: 7 | Journal Article |

Cited by: Papers (2)

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Federated learning (FL) deployed in the edge network environment is a promising approach for combining the separated training results based on the isolated local data sensed by various Internet of Things (IoT) devices. However, the limited computing resources for the training of various application models in each edge server and the communication burden among the edge server and numerous IoT devic...Show More

Transform-Domain Federated Learning for Edge-Enabled IoT Intelligence

Lei Zhao;Lin Cai;Wu-Sheng Lu

IEEE Internet of Things Journal

Year: 2023 | Volume: 10, Issue: 7 | Journal Article |

Smart Resource Allocation for Mobile Edge Computing: A Deep Reinforcement Learning Approach

Jiadai Wang;Lei Zhao;Jiajia Liu;Nei Kato

IEEE Transactions on Emerging Topics in Computing

Year: 2021 | Volume: 9, Issue: 3 | Journal Article |

Cited by: Papers (316)

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The development of mobile devices with improving communication and perceptual capabilities has brought about a proliferation of numerous complex and computation-intensive mobile applications. Mobile devices with limited resources face more severe capacity constraints than ever before. As a new concept of network architecture and an extension of cloud computing, Mobile Edge Computing (MEC) seems to...Show More

Smart Resource Allocation for Mobile Edge Computing: A Deep Reinforcement Learning Approach

Jiadai Wang;Lei Zhao;Jiajia Liu;Nei Kato

IEEE Transactions on Emerging Topics in Computing

Year: 2021 | Volume: 9, Issue: 3 | Journal Article |

Adaptive Content Placement in Edge Networks Based on Hybrid User Preference Learning

Lei Zhao;Xiaolong Lan;Lin Cai;Jianping Pan

2019 IEEE Global Communications Conference (GLOBECOM)

Year: 2019 | Conference Paper |

Cited by: Papers (4)

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Edge caching is promising to alleviate the backhaul pressure and provide low latency delivery for delay sensitive applications. However, it encounters great challenges to make adaptive content placement decisions according to the scattered explicit feedback with spatial and temporal dynamics. We propose a hybrid learning framework to obtain a more accurate prediction of users' preference by combin...Show More

Adaptive Content Placement in Edge Networks Based on Hybrid User Preference Learning

Lei Zhao;Xiaolong Lan;Lin Cai;Jianping Pan

2019 IEEE Global Communications Conference (GLOBECOM)

Year: 2019 | Conference Paper |

Routing for Crowd Management in Smart Cities: A Deep Reinforcement Learning Perspective

Lei Zhao;Jiadai Wang;Jiajia Liu;Nei Kato

IEEE Communications Magazine

Year: 2019 | Volume: 57, Issue: 4 | Magazine Article |

Cited by: Papers (104)

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The concept of smart city has been flourishing based on the prosperous development of various advanced technologies: mobile edge computing (MEC), ultra-dense networking, and software defined networking. However, it becomes increasingly complicated to design routing strategies to meet the stringent and ever changing network requirements due to the dynamic distribution of the crowd in different sect...Show More

Routing for Crowd Management in Smart Cities: A Deep Reinforcement Learning Perspective

Lei Zhao;Jiadai Wang;Jiajia Liu;Nei Kato

IEEE Communications Magazine

Year: 2019 | Volume: 57, Issue: 4 | Magazine Article |

Optimal Edge Resource Allocation in IoT-Based Smart Cities

Lei Zhao;Jiadai Wang;Jiajia Liu;Nei Kato

Year: 2019 | Volume: 33, Issue: 2 | Magazine Article |

Cited by: Papers (115)

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With IoT-based smart cities, massive heterogeneous IoT devices are running diverse advanced services for unprecedented intelligence and efficiency in various domains of city life. Given the exponentially growing number of IoT devices and the large number of smart city services as well as their different QoS requirements, it has been a big challenge for servers to optimally allocate limited resourc...Show More

Optimal Edge Resource Allocation in IoT-Based Smart Cities

Lei Zhao;Jiadai Wang;Jiajia Liu;Nei Kato

Year: 2019 | Volume: 33, Issue: 2 | Magazine Article |

Big Data Acquisition Under Failures in FiWi Enhanced Smart Grid

Hongzhi Guo;Jiajia Liu;Lei Zhao

IEEE Transactions on Emerging Topics in Computing

Year: 2019 | Volume: 7, Issue: 3 | Journal Article |

Cited by: Papers (30)

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With the increasing of monitoring devices and advanced measurement infrastructures, smart grids (SGs) collect large amounts of data every moment, which gives rise to the SG big data. In order to fulfill diverse communication requirements of various energy-related data in SG, it is obviously impractical to rely on a single communication technology, and a hybrid communication architecture of low-lat...Show More

Big Data Acquisition Under Failures in FiWi Enhanced Smart Grid

Hongzhi Guo;Jiajia Liu;Lei Zhao

IEEE Transactions on Emerging Topics in Computing

Year: 2019 | Volume: 7, Issue: 3 | Journal Article |

Gateway Placement for Reliability Optimization in 5G-Satellite Hybrid Networks

Yurui Cao;Lei Zhao;Yongpeng Shi;Jiajia Liu

2018 International Conference on Computing, Networking and Communications (ICNC)

Year: 2018 | Conference Paper |

Cited by: Papers (8)

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The placement of satellite gateways, as critical devices for data transmission between terrestrial networks and satellites, is of fundamental importance for the design of 5G-satellite hybrid networks, especially for the network reliability since the satellite links are prone to failing due to poor meteorological conditions. To the best of our knowledge, this problem almost remains untouched. Exist...Show More

Gateway Placement for Reliability Optimization in 5G-Satellite Hybrid Networks

Yurui Cao;Lei Zhao;Yongpeng Shi;Jiajia Liu

2018 International Conference on Computing, Networking and Communications (ICNC)

Year: 2018 | Conference Paper |

Optimal Placement of Cloudlets for Access Delay Minimization in SDN-Based Internet of Things Networks

Lei Zhao;Wen Sun;Yongpeng Shi;Jiajia Liu

IEEE Internet of Things Journal

Year: 2018 | Volume: 5, Issue: 2 | Journal Article |

Cited by: Papers (100)

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Given the highly dynamic traffic loads of mobile Internet of Things (IoT) devices and their stringent quality-ofservice requirements, i.e., access delay particularly, as well as the heterogeneous infrastructures among IoT networks, it is a nontrivial task to efficiently deploy cloudlets among large number of access points (APs) in IoT networks, especially for the access delay and network reliabili...Show More

Optimal Placement of Cloudlets for Access Delay Minimization in SDN-Based Internet of Things Networks

Lei Zhao;Wen Sun;Yongpeng Shi;Jiajia Liu

IEEE Internet of Things Journal

Year: 2018 | Volume: 5, Issue: 2 | Journal Article |

Optimal Placement of Virtual Machines for Supporting Multiple Applications in Mobile Edge Networks

Lei Zhao;Jiajia Liu

IEEE Transactions on Vehicular Technology

Year: 2018 | Volume: 67, Issue: 7 | Journal Article |

Cited by: Papers (55)

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Although mobile edge computing (MEC), as an extension of the cloud computing paradigm to edge networks, overcomes some obstacles of traditional mobile cloud computing, i.e., the reduced response time particularly, it is a nontrivial task to efficiently deploy virtual machine replica copies (VRCs) supporting multiple applications among numerous MEC servers in edge networks. To combat this issue, we...Show More

Optimal Placement of Virtual Machines for Supporting Multiple Applications in Mobile Edge Networks

Lei Zhao;Jiajia Liu

IEEE Transactions on Vehicular Technology

Year: 2018 | Volume: 67, Issue: 7 | Journal Article |

Joint Placement of Controllers and Gateways in SDN-Enabled 5G-Satellite Integrated Network

Jiajia Liu;Yongpeng Shi;Lei Zhao;Yurui Cao;Wen Sun;Nei Kato

IEEE Journal on Selected Areas in Communications

Year: 2018 | Volume: 36, Issue: 2 | Journal Article |

Cited by: Papers (148)

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Leveraging the concept of software-defined network (SDN), the integration of terrestrial 5G and satellite networks brings us lots of benefits. The placement problem of controllers and satellite gateways is of fundamental importance for design of such SDN-enabled integrated network, especially, for the network reliability and latency, since different placement schemes would produce various network ...Show More

Joint Placement of Controllers and Gateways in SDN-Enabled 5G-Satellite Integrated Network

Jiajia Liu;Yongpeng Shi;Lei Zhao;Yurui Cao;Wen Sun;Nei Kato

IEEE Journal on Selected Areas in Communications

Year: 2018 | Volume: 36, Issue: 2 | Journal Article |

Optimal Placement of Virtual Machines in Mobile Edge Computing

Lei Zhao;Jiajia Liu;Yongpeng Shi;Wen Sun;Hongzhi Guo

GLOBECOM 2017 - 2017 IEEE Global Communications Conference

Year: 2017 | Conference Paper |

Cited by: Papers (26)

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Mobile edge computing (MEC), as an extension of the cloud computing paradigm to the edge network, is a promising solution to provide resource-intensive and time-critical applications to mobile users. It overcomes some obstacles of traditional mobile cloud computing by offering ultra-short latency and less core network traffic. This paper proposes a new framework based on the architecture of MEC to...Show More

Optimal Placement of Virtual Machines in Mobile Edge Computing

Lei Zhao;Jiajia Liu;Yongpeng Shi;Wen Sun;Hongzhi Guo

GLOBECOM 2017 - 2017 IEEE Global Communications Conference

Year: 2017 | Conference Paper |

Resilient and Low-Latency Information Acquisition for FiWi Enhanced Smart Grid

Jiajia Liu;Hongzhi Guo;Lei Zhao

Year: 2017 | Volume: 31, Issue: 5 | Magazine Article |

Cited by: Papers (12)

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As distinct SG applications have different communication requirements in terms of reliability, latency, bandwidth, and so on, it is obviously infeasible to rely on a single communication technology for SG communications. Therefore, a hybrid communication architecture integrating both low latency fiber optic and flexible wireless technologies should be a promising candidate, which gives rise to the...Show More

Resilient and Low-Latency Information Acquisition for FiWi Enhanced Smart Grid

Jiajia Liu;Hongzhi Guo;Lei Zhao

Year: 2017 | Volume: 31, Issue: 5 | Magazine Article |

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