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Pattern-Sensitive Local Differential Privacy for Finite-Range Time-Series Data in Mobile Crowdsensing
Zhetao Li;Xiyu Zeng;Yong Xiao;Chengxin Li;Wentai Wu;Haolin Liu
Publication Year: 2025,Page(s):1 - 14
Time-series data is crucial for the development of mobile crowdsensing (MCS). Participant’s privacy is one of the major concerns because MCS data often contain sensitive individual information. Existing privacy-preserving mechanisms for time-series data do not preserve salient patterns of the time series and take into account that the perturbed data may fall outside the valid data interval, leadin...Show More
WordWhisper: Exploiting Real-Time, Hardware-Dependent IoT Communication Against Eavesdropping
Publication Year: 2025,Page(s):15 - 29
Secure protocol-independent communication is increasingly demanding to support information exchange among neighbor Internet of Things (IoT) devices. For example, recent works utilize ultrasound at the resonant frequency range of a gyroscope to build communication between a speaker and the gyroscope. However, they are vulnerable to eavesdropping attacks and may have limitations in communication del...Show More
Distributed Age-of-Information Scheduling With NOMA via Deep Reinforcement Learning
Congwei Zhang;Yifei Zou;Zuyuan Zhang;Dongxiao Yu;Jorge Torres Gómez;Tian Lan;Falko Dressler;Xiuzhen Cheng
Publication Year: 2025,Page(s):30 - 44
Many emerging applications in edge computing require processing of huge volumes of data generated by end devices, using the freshest available information. In this paper, we address the distributed optimization of multi-user long-term average Age-of-Information (AoI) objectives in edge networks that use NOMA transmission. This poses a challenge of non-convex online optimization, which in existing ...Show More
LI2: A New Learning-Based Approach to Timely Monitoring of Points-of-Interest With UAV
Ziyao Huang;Weiwei Wu;Kui Wu;Hang Yuan;Chenchen Fu;Feng Shan;Jianping Wang;Junzhou Luo
Publication Year: 2025,Page(s):45 - 61
Unmanned aerial vehicles (UAVs) play a critical role in disaster response, swiftly gathering information from various points-of-interest (PoIs) across extensive areas. The freshness of this information is measured by the age of information (AoI), representing the time since the latest information acquisition of a specific PoI. However, devising AoI-minimizing routes for UAVs in obstructed post-dis...Show More
Design and Performance of Resonant Beam Communications—Part I: Quasi-Static Scenario
Dongxu Li;Yuanming Tian;Chuan Huang;Qingwen Liu;Shengli Zhou
Publication Year: 2025,Page(s):62 - 71
Cited by: Papers (1)
This two-part paper studies a point-to-point resonant beam communication (RBCom) system, where two separately deployed retroreflectors are adopted to generate the resonant beam between the transmitter and the receiver, and analyzes the transmission rate of the considered system under both the quasi-static and mobile scenarios. Part I of this paper focuses on the quasi-static scenario where the loc...Show More
Ambient Light Reflection-Based Eavesdropping Enhanced With cGAN
Guoming Zhang;Heqiang Fu;Zhijie Xiang;Xinyan Zhou;Pengfei Hu;Xiuzhen Cheng;Yanni Yang
Publication Year: 2025,Page(s):72 - 85
Sound eavesdropping using light has been an area of considerable interest and concern, as it can be achieved over long distances. However, previous work has often lacked stealth (e.g., active emission of laser beams) or been limited in the range of realistic applications (e.g., using direct light from a device’s indicator LED or a hanging light bulb). In this paper, we present EchoLight, a non-int...Show More
Network-Wide Data Collection Based on In-Band Network Telemetry for Digital Twin Networks
Publication Year: 2025,Page(s):86 - 101
Cited by: Papers (1)
The Digital Twin Network (DTN) establishes a real-time virtual mirror of physical networks. Data collection plays an essential role in DTN, which collects the status data of physical network for building highly consistent digital twins. In this paper, we present a network-wide data collection scheme based on In-band Network Telemetry (INT). To build a lifelike mirror of the physical network, the p...Show More
P3ID: A Privacy-Preserving Person Identification Framework Towards Multi-Environments Based on Transfer Learning
Hanxiang He;Xintao Huan;Jing Wang;Yong Luo;Han Hu;Jianping An
Publication Year: 2025,Page(s):102 - 116
Concerns surrounding privacy leakages caused by prevalent vision-based person identifications are countless. A promising privacy-preserving solution is to identify the wireless signals reflecting persons, which, however, faces a major challenge of losing efficacy in multi-environments. In this paper, we work on person identification based on wireless signals using transfer learning, toward tacklin...Show More
Argus: Enabling Cross-Camera Collaboration for Video Analytics on Distributed Smart Cameras
Publication Year: 2025,Page(s):117 - 134
Overlapping cameras offer exciting opportunities to view a scene from different angles, allowing for more advanced, comprehensive and robust analysis. However, existing video analytics systems for multi-camera streams are mostly limited to (i) per-camera processing and aggregation and (ii) workload-agnostic centralized processing architectures. In this paper, we present Argus, a distributed video ...Show More
t-READi: Transformer-Powered Robust and Efficient Multimodal Inference for Autonomous Driving
Pengfei Hu;Yuhang Qian;Tianyue Zheng;Ang Li;Zhe Chen;Yue Gao;Xiuzhen Cheng;Jun Luo
Publication Year: 2025,Page(s):135 - 149
Given the wide adoption of multimodal sensors (e.g., camera, lidar, radar) by autonomous vehicles (AVs), deep analytics to fuse their outputs for a robust perception become imperative. However, existing fusion methods often make two assumptions rarely holding in practice: i) similar data distributions for all inputs and ii) constant availability for all sensors. Because, for example, lidars have v...Show More
The Structure of Hypergraphs Arising in Cellular Mobile Communication Systems
Publication Year: 2025,Page(s):150 - 164
An assumption that researchers have often used to model interference in a wireless network is the unit disk graph model. While many theoretical results and performance guarantees have been obtained under this model, an open research direction is to extend these results to hypergraph interference models. Motivated by recent results that the worst-case performance of the distributed maximal scheduli...Show More
The Structure of Hypergraphs Arising in Cellular Mobile Communication Systems
Year: 2025 | Volume: 24 | Issue: 1
Budget-Constrained Digital Twin Synchronization and Its Application on Fidelity-Aware Queries in Edge Computing
Publication Year: 2025,Page(s):165 - 182
With the advance of mobile edge computing (MEC) and the Internet of Things (IoT), digital twin (DT) has become an emerging technology for provisioning IoT services between the real world and the cyber world. In this paper, we consider the state updating of DTs in an MEC network through synchronizing DTs with their physical objects. We make use of an energy-constrained UAV for data collection in a ...Show More
Blockchain-Aided Digital Twin Offloading Mechanism in Space-Air-Ground Networks
Yongkang Gong;Haipeng Yao;Zehui Xiong;C. L. Philip Chen;Dusit Niyato
Publication Year: 2025,Page(s):183 - 197
Cited by: Papers (2)
Space-air-ground (SAG) integrated heterogenous networks can provide pervasive intelligence services for various ground users (GUs). The network can help cellular networks release network resources and alleviate congestion pressure. Moreover, one important application of the network is that digital twin (DT) can enable nearly-instant wireless connectivity and highly-reliable data mapping from physi...Show More
PHCG: PLC Honeypoint Communication Generator for Industrial IoT
Hao Liu;Yinghai Zhou;Binxing Fang;Yanbin Sun;Ning Hu;Zhihong Tian
Publication Year: 2025,Page(s):198 - 209
With the rapid development of mobile and wireless technologies, the industrial manufacturing sector has entered the era of automation. The proliferation of mobile devices, sensor networks, and remote monitoring systems enables factory equipment to be more flexibly connected and controlled. However, the trend towards industrial networks also brings new challenges. Industrial control systems (ICSs) ...Show More
Joint Optimization of Device Placement and Model Partitioning for Cooperative DNN Inference in Heterogeneous Edge Computing
Publication Year: 2025,Page(s):210 - 226
EdgeAI represents a compelling approach for deploying DNN models at network edge through model partitioning. However, most existing partitioning strategies have primarily concentrated on homogeneous environments, neglecting the effect of device placement and their inapplicability to heterogeneous settings. Moreover, these strategies often rely on either data parallelism or model parallelism, each ...Show More
Romeo: Fault Detection of Rotating Machinery via Fine-Grained mmWave Velocity Signature
Yanni Yang;Pengfei Hu;Jun Luo;Zhenlin An;Jiannong Cao;Dongxiao Yu;Xiuzhen Cheng
Publication Year: 2025,Page(s):227 - 242
Real-time velocity monitoring is pivotal for fault detection of rotating machinery. However, existing methods rely on either troublesome deployments of optical encoders and IMU sensors or various tachometers delivering coarse-grained velocity measurements insufficient for fault detection. To overcome these limitations, we propose Romeo as the first work to exploit the mmWave radar for rotating mac...Show More
Traffic Load-Aware Resource Management Strategy for Underwater Wireless Sensor Networks
Publication Year: 2025,Page(s):243 - 260
Underwater Wireless Sensor Networks (UWSNs) represent a promising technology that enables diverse underwater applications through acoustic communication. However, it encounters significant challenges including harsh communication environments, limited energy supply, and restricted signal transmission. This paper aims to provide efficient and reliable communication in underwater networks with limit...Show More
To guarantee the reliability for WRSNs, placing sufficient static chargers effectively ensures charging coverage for the entire network. However, this approach leads to a considerable number of sensors located within charging overlaps. The destructive wave interference caused by concurrent charging in these overlaps may weaken sensors received power, thereby negatively impacting charging performan...Show More
Secure Two-Party Frequent Itemset Mining With Guaranteeing Differential Privacy
Publication Year: 2025,Page(s):276 - 292
Cited by: Papers (1)
Frequent itemset mining is an essential task in data analysis. Therefore, it is crucial to design practical methods for privacy-preserving frequent itemset mining, enabling private data analysis. For two-party data analysis tasks, each party possesses its portion of the data and is reluctant to share the data with the other. While secure computation can enable two-party frequent itemset mining, th...Show More
Scrava: Super Resolution-Based Bandwidth-Efficient Cross-Camera Video Analytics
Publication Year: 2025,Page(s):293 - 305
Massively deployed cameras form a tightly connected network which generates video streams continuously. Benefiting from advances in computer vision, automated real-time analytics of video streams can be of practical value in various scenarios. As cameras become more dense, cross-camera video analytics has emerged. Combining video contents from multiple cameras for analytics is certainly more promi...Show More
Scrava: Super Resolution-Based Bandwidth-Efficient Cross-Camera Video Analytics
Year: 2025 | Volume: 24 | Issue: 1
Combinatorial Data Augmentation: A Key Enabler to Bridge Geometry- and Data-Driven WiFi Positioning
Seung Min Yu;Kyuwon Han;Jihong Park;Seong-Lyun Kim;Seung-Woo Ko
Publication Year: 2025,Page(s):306 - 320
Cited by: Papers (1)
Due to the emergence of various wireless sensing technologies, numerous positioning algorithms have been introduced in the literature, categorized into geometry-driven positioning (GP) and data-driven positioning (DP). These approaches have respective limitations, e.g., a non-line-of-sight issue for GP and the lack of a high-dimensional and labeled dataset for DP, which could be complemented by in...Show More
Knowledge-Aware Parameter Coaching for Communication-Efficient Personalized Federated Learning in Mobile Edge Computing
Mingjian Zhi;Yuanguo Bi;Lin Cai;Wenchao Xu;Haozhao Wang;Tianao Xiang;Qiang He
Publication Year: 2025,Page(s):321 - 337
Personalized Federated Learning (pFL) can improve the accuracy of local models and provide enhanced edge intelligence without exposing the raw data in Mobile Edge Computing (MEC). However, in the MEC environment with constrained communication resources, transmitting the entire model between the server and the clients in traditional pFL methods imposes substantial communication overhead, which can ...Show More
Physical-Layer CTC From BLE to Wi-Fi With IEEE 802.11ax
Demin Gao;Liyuan Ou;Yongrui Chen;Xiuzhen Guo;Ruofeng Liu;Yunhuai Liu;Tian He
Publication Year: 2025,Page(s):338 - 351
Cited by: Papers (2)
Wi-Fi is the de facto standard for providing wireless access to the Internet in the 2.4 GHz ISM band. Tens of billions of Wi-Fi devices (e.g., smartphones) have been shipped worldwide with limited types of wireless radios operating only when Wi-Fi connectivity is available, making it challenging to access data in heterogeneous IoT devices. However, the direct connection between Wireless Personal A...Show More
Near-Field Beam Training for Extremely Large-Scale MIMO Based on Deep Learning
Publication Year: 2025,Page(s):352 - 362
Extremely Large-scale Array (ELAA) is considered a frontier technology for future communication systems, playing a crucial role in enhancing the rate and spectral efficiency of wireless networks. As ELAA employs a multitude of antennas operating at higher frequencies, users are typically situated in the near-field region where the spherical wavefront propagates. Near-field beam training requires i...Show More
Multi-User Task Offloading in UAV-Assisted LEO Satellite Edge Computing: A Game-Theoretic Approach
Publication Year: 2025,Page(s):363 - 378
Unmanned Aerial Vehicle (UAV)-assisted Low Earth Orbit (LEO) satellite edge computing (ULSE) networks can address the challenge communications issues in areas with harsh terrain and achieve global wireless coverage to provide services for mobile user devices (MUDs). This paper studies the LEO-UAV task offloading problem where MUDs compete for limited resources in the ULSE networks. We formulate th...Show More
Contact Information
Editor-in-Chief
Jie Xu
Associate Editor-in-Chief
The Chinese University of Hong Kong
Shenzhen
China
xujie@cuhk.edu.cnEditor-in-Chief
Associate Editor-in-Chief
Ohio State University, Department of Electrical and Computer Engineering
Columbus
USA
tmc-eic@computer.orgContact Information
Editor-in-Chief
Jie Xu
Associate Editor-in-Chief
The Chinese University of Hong Kong
Shenzhen
China
xujie@cuhk.edu.cnEditor-in-Chief
Associate Editor-in-Chief
Ohio State University, Department of Electrical and Computer Engineering
Columbus
USA
tmc-eic@computer.orgIEEE Account
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