172 citations · 270 across the 14 of their papers we have counts for
14 papers
SI-ChainFL: Shapley-Incentivized Secure Federated Learning for High-Speed Rail Data Sharing
Mingjie Zhao, Cheng Dai, Fei Chen +4
In high-speed rail (HSR) systems, federated learning (FL) enables cross-departmental flow prediction without sharing raw data. However, existing schemes suffer from two key limitat…
HoGS: Homophily-Oriented Graph Synthesis for Local Differentially Private GNN Training
Wen Xu, Zhetao Li, Yong Xiao +3
Graph neural networks (GNNs) have demonstrated remarkable performance in various graph-based machine learning tasks by effectively modeling high-order interactions between nodes. H…
Truthful and Trustworthy IoT AI Agents via Immediate-Penalty Enforcement under Approximate VCG Mechanisms
Xun Shao, Ryuuto Shimizu, Zhi Liu +2
The deployment of autonomous AI agents in Internet of Things (IoT) energy systems requires decision-making mechanisms that remain robust, efficient, and trustworthy under real-time…
An Efficient Imbalance-Aware Federated Learning Approach for Wearable Healthcare with Autoregressive Ratio Observation
Wenhao Yan, He Li, Kaoru Ota +1
Widely available healthcare services are now getting popular because of advancements in wearable sensing techniques and mobile edge computing. People's health information is collec…
Wital: A COTS WiFi Devices Based Vital Signs Monitoring System Using NLOS Sensing Model
Xiang Zhang, Yu Gu, Huan Yan +5
Vital sign (breathing and heartbeat) monitoring is essential for patient care and sleep disease prevention. Most current solutions are based on wearable sensors or cameras; however…
Device-Bind Key-Storageless Hardware AI Model IP Protection: A PUF and Permute-Diffusion Encryption-Enabled Approach
Qianqian Pan, Mianxiong Dong, Kaoru Ota +1
Machine learning as a service (MLaaS) framework provides intelligent services or well-trained artificial intelligence (AI) models for local devices. However, in the process of mode…
UAV Base Station Trajectory Optimization Based on Reinforcement Learning in Post-disaster Search and Rescue Operations
Shiye Zhao, Kaoru Ota, Mianxiong Dong
Because of disaster, terrestrial base stations (TBS) would be partly crashed. Some user equipments (UE) would be unserved. Deploying unmanned aerial vehicles (UAV) as aerial base s…
Deep Reinforcement Learning Based Multi-Access Edge Computing Schedule for Internet of Vehicle
Xiaoyu Dai, Kaoru Ota, Mianxiong Dong
As intelligent transportation systems been implemented broadly and unmanned arial vehicles (UAVs) can assist terrestrial base stations acting as multi-access edge computing (MEC) t…
Clairvoyance: Intelligent Route Planning for Electric Buses Based on Urban Big Data
Xiangyong Lu, Kaoru Ota, Mianxiong Dong +2
Nowadays many cities around the world have introduced electric buses to optimize urban traffic and reduce local carbon emissions. In order to cut carbon emissions and maximize the…
A Game-Theoretic Approach to Energy-Efficient Resource Allocation in Device-to-Device Underlay Communications
Zhenyu Zhou, Mianxiong Dong, Kaoru Ota +3
Despite the numerous benefits brought by Device-to-Device (D2D) communications, the introduction of D2D into cellular networks poses many new challenges in the resource allocation…
Energy Efficiency and Spectral Efficiency Tradeoff in Device-to-Device (D2D) Communications
Zhenyu Zhou, Mianxiong Dong, Kaoru Ota +2
In this letter, we investigate the tradeoff between energy efficiency (EE) and spectral efficiency (SE) in device-to-device (D2D) communications underlaying cellular networks with…
HVSTO: Efficient Privacy Preserving Hybrid Storage in Cloud Data Center
Mianxiong Dong, He Li, Kaoru Ota +1
In cloud data center, shared storage with good management is a main structure used for the storage of virtual machines (VM). In this paper, we proposed Hybrid VM storage (HVSTO), a…
NetSecCC: A Scalable and Fault-tolerant Architecture without Outsourcing Cloud Network Security
Jin He, Mianxiong Dong, Kaoru Ota +2
Modern cloud computing platforms based on virtual machine monitors carry a variety of complex business that present many network security vulnerabilities. At present, the tradition…
Distributed Interference-Aware Energy-Efficient Resource Allocation for Device-to-Device Communications Underlaying Cellular Networks
Zhenyu Zhou, Mianxiong Dong, Kaoru Ota +2
The introduction of device-to-device (D2D) into cellular networks poses many new challenges in the resource allocation design due to the co-channel interference caused by spectrum…