检索结果-内蒙古大学图书馆

Preserving Location Privacy of IoT Devices in Heterogeneous Edge computing Architecture Through Deniability-Based Authentication

引用

IEEE Transactions on Consumer Electronics 2025年

作者： Ali, Ikram Li, Jianqiang Chen, Jie Chen, Yong Ullah, Shamsher Wakeel, Abdul Shenzhen University National Engineering Laboratory of Big Data System Computing Technology Shenzhen518060 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China National University of Sciences and Technology Military College of Signals Department of Electrical Engineering Islamabad Pakistan

Edge computing moves cloud services closer to consumer Internet of Things (IoT) devices, reducing latency and bandwidth usage. This setup enables faster responses but also introduces new security challenges, particularly concerning location privacy when sender and receiver use different security techniques. The authentication process in such architectures can expose the location of IoT devices. To address this issue, researchers have proposed various privacy-preserving schemes. However, these are computationally heavy for IoT devices. To tackle this issue, we propose two novel heterogeneous deniable authentication schemes: HDA-IoT-I and HDA-IoT-II. These schemes use public-key infrastructure and identity-based cryptography to protect the location privacy of IoT devices in heterogeneous edge computing environments. Our schemes enable the designated edge device to verify the source of a message without being able to prove its origin to a third party, thus preserving privacy. Additionally, they incorporate a batch verification method, which speeds up the verification of multiple deniable authenticators. The proposed schemes are formally proven secure in the random oracle model based on the hardness assumption of elliptic curve inverse computational Diffie-Hellman problem. The performance evaluation demonstrate that our schemes significantly enhance computational and communication efficiency, making them suitable for IoT devices. © 2025 IEEE.

关键词： Differential privacy

来源：评论

学校读者我要写书评

暂无评论

HSD-PAM: High Speed Super Resolution Deep Penetration Photoacoustic Microscopy Imaging Boosted by Dual Branch Fusion Network

arXiv

引用

arXiv 2023年

作者： Zhang, Zhengyuan Jin, Haoran Zheng, Zesheng Zhang, Wenwen Lu, Wenhao Qin, Feng Sharma, Arunima Pramanik, Manojit Zheng, Yuanjin The School of Electrical and Electronic Engineering Nanyang Technological University Singapore Zhejiang University College of Mechanical Engineering The State Key Laboratory of Fluid Power and Mechatronic Systems Hangzhou China Johns Hopkins University Electrical and Computer Engineering Baltimore United States Iowa State University Department of Electrical and Computer Engineering AmesIA United States

Photoacoustic microscopy (PAM) is a novel implementation of photoacoustic imaging (PAI) for visualizing the 3D bio-structure, which is realized by raster scanning of the tissue. However, as three involved critical imaging parameters, imaging speed, lateral resolution, and penetration depth have mutual effect to one the other. The improvement of one parameter results in the degradation of other two parameters, which constrains the overall performance of the PAM system. Here, we propose to break these limitations by hardware and software co-design. Starting with low lateral resolution, low sampling rate AR-PAM imaging which possesses the deep penetration capability, we aim to enhance the lateral resolution and up sampling the images, so that high speed, super resolution, and deep penetration for the PAM system (HSD-PAM) can be achieved. Data-driven based algorithm is a promising approach to solve this issue, thereby a dedicated novel dual branch fusion network is proposed, which includes a high resolution branch and a high speed branch. Since the availability of switchable AR-OR-PAM imaging system, the corresponding low resolution, undersample AR-PAM and high resolution, full sampled OR-PAM image pairs are utilized for training the network. Extensive simulation and in vivo experiments have been conducted to validate the trained model, enhancement results have proved the proposed algorithm achieved the best perceptual and quantitative image quality. As a result, the imaging speed is increased 16× times and the imaging lateral resolution is improved 5× times, while the deep penetration merit of AR-PAM modality is still reserved. © 2023, CC BY-NC-ND.

关键词： Photoacoustic microscopy

来源：评论

学校读者我要写书评

暂无评论

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning

arXiv

引用

arXiv 2025年

作者： Yang, Xiaohong Liwang, Minghui Wang, Xianbin Cheng, Zhipeng Hosseinalipour, Seyyedali Dai, Huaiyu Jiao, Zhenzhen School of Informatics Xiamen University Fujian China Department of Control Science and Engineering The National Key Laboratory of Autonomous Intelligent Unmanned Systems Japan Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Tongji University Shanghai China Department of Electrical and Computer Engineering Western University ON Canada School of Future Science and Engineering Soochow University Suzhou China Department of Electrical Engineering University at Buffalo-SUNY BuffaloNY United States Department of Electrical and Computer Engineering NC State University RaleighNC United States iF-Labs Beijing Teleinfo Technology Company Ltd. CAICT Beijing China

The rapid growth of AI-enabled Internet of Vehicles (IoV) calls for efficient machine learning (ML) solutions that can handle high vehicular mobility and decentralized data. This has motivated the emergence of Hierarchical Federated Learning over vehicle-edge-cloud architectures (VEC-HFL). Nevertheless, one aspect which is underexplored in the literature on VEC-HFL is that vehicles often need to execute multiple ML tasks simultaneously, where this multi-model training environment introduces crucial challenges. First, improper aggregation rules can lead to model obsolescence and prolonged training times. Second, vehicular mobility may result in inefficient data utilization by preventing the vehicles from returning their models to the network edge. Third, achieving a balanced resource allocation across diverse tasks becomes of paramount importance as it majorly affects the effectiveness of collaborative training. We take one of the first steps towards addressing these challenges via proposing a framework for multi-model training in dynamic VEC-HFL with the goal of minimizing global training latency while ensuring balanced training across various tasks—a problem that turns out to be NP-hard. To facilitate timely model training, we introduce a hybrid synchronous-asynchronous aggregation rule. Building on this, we present a novel method called Hybrid Evolutionary And gReedy allocaTion (HEART). The framework operates in two stages: first, it achieves balanced task scheduling through a hybrid heuristic approach that combines improved Particle Swarm Optimization (PSO) and Genetic Algorithms (GA);second, it employs a low-complexity greedy algorithm to determine the training priority of assigned tasks on vehicles. Experiments on real-world datasets demonstrate the superiority of HEART over existing methods. © 2025, CC BY-NC-ND.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Advanced Data Association Technique Using Integrated Track Splitting Filter for Multi-Target Tracking in Clutter and Occlusion

SSRN

引用

SSRN 2024年

作者： Memon, Sufyan Ali Ullah, Ihsan Ullah, Inam Noor, Adeeb Chungbuk National University Korea Republic of Department of Defense Systems Engineering Sejong University Gwangjin-Gu Seoul05006 Korea Republic of Department of Electrical and Computer Engineering COMSATS University Islamabad Abbottabad22060 Pakistan Department of Computer Engineering Gachon University Seongnam13120 Korea Republic of Department of Information Technology Faculty of Computing and Information Technology King AbdulAziz University Jeddah80221 Saudi Arabia

Due to the unknown number of actual targets, their motion uncertainties, and the coalescence nature of measurements, the multi-target tracking (MTT) becomes a challenging problem. The traditional MTT methods face intractable computational complexities because they use a joint data association approach that enumerates an exponentially increasing number of joint measurements-to-track hypotheses and iteratively obtains their a-posteriori probabilities, exhausting enough computational memory. Thus, the advanced intelligent tracking system demands avoiding the joint data association procedure. To solve such problems, the joint measurement data association probabilities are adjusted by its track likelihood ratio, detection and gating probabilities which significantly decreases the number of false measurement detections. Due to plenty of observation data received from sensor (such as radar), the position and velocity errors of targets become prominent. Therefore, we adjust the threshold of measurement selection which develops a stable validation gate consisting of effective measurement detections. The proposed modified data association approach is applied to the multi-scan integrated track splitting algorithm (MITS) to improve tracking performance of ITS for both single and multi-maneuvering-targets in a clutter and occlusion environment. The false track discrimination (FTD) and estimation accuracy of the proposed MITS method are verified using the Monte-Carlo simulation in comparison to the standard ITS algorithm. © 2024, The Authors. All rights reserved.

关键词： Monte Carlo methods

来源：评论

学校读者我要写书评

暂无评论

AFML: An Asynchronous Federated Meta-Learning Mechanism for Charging Station Occupancy Prediction with Biased and Isolated Data

引用

IEEE Transactions on Big Data 2024年

作者： Chen, Qiyang Li, Han You, Linlin Qu, Haohao Abdelmoniem, Ahmed M. Yuen, Chau Sun Yat-Sen University School of Intelligent Systems Engineering Shenzhen510006 China Hong Kong Polytechnic University Department of Computing Hong Kong100872 Hong Kong Queen Mary University of London Department of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom Assiut University Department of Computer Science Assiut71515 Egypt Nanyang Technological University School of Electrical and Electronics Engineering Singapore639798 Singapore

Electric vehicles (EVs) are driving green and low-carbon transport in modern cities. It makes charging station occupancy prediction (CSOP) critual for intelligent transportation systems (ITS) to achieve a balance between the supply and demand in resolving the dynamics between EVs and changing stations. Even though several big data-based solutions have been discussed, they are still struggling to collaboratively utilize heterogeneous data and distributed computing resources located at both physically and logicially isolated charging stations to better support context-driven CSOP. To addres this challenge, we propose an Asynchronous Federated Meta-learning Mechanism (AFML) for CSOP, which can train a meta-model with strong adaptation ability in an asynchronous and collaborative manner. In general, it incorporates an adaptive reptile algorithm (AR) and an weighted aggregation strategy (WA) to jointly ensure the training efficiency and model adaptivity. Evaluations on real-world CSOP datasets demonstrate that compared to the second best method, AFML can significantly improve forecasting accuracy by 14%, accelerate model convergence by 9% and enhance model generalizability by 10%, illustrating its merits in support CSOP to embrace a smart and sustainable city. © 2015 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Eltrack: Correlating Events and Language for Visual Tracking

SSRN

引用

SSRN 2024年

作者： Alansari, Mohamad Alnuaimi, Khaled Alansari, Sara Werghi, Naoufel Javed, Sajid Department of Electrical Engineering College Of Computing And Mathematical Sciences Department of Computer Science Khalifa University Abu Dhabi United Arab Emirates Center for Autonomous Robotic Systems Khalifa University Abu Dhabi United Arab Emirates Center for Cyber-Physical Systems Khalifa University Abu Dhabi United Arab Emirates

The reliance on visible cameras in Visual Object Tracking (VOT) presents challenges in handling rapid object movements and illumination variations. In contrast, event cameras, inspired by biological vision systems, capture asynchronous and sparse events with significantly lower latency. While visible cameras excel in perceiving texture details and slow motion, event cameras offer advantages such as freedom from motion blur and a larger dynamic range, making them suitable for fast motion and low illumination scenarios. Integrating these two sensor modalities can enhance the reliability of object *** paper addresses key challenges in event-based tracking and tracking by language descriptions. First, we tackle the scarcity of large-scale event-based benchmarks by leveraging the \textit{v2e} toolbox to synthesize event data from eight conventional frame-based benchmarks. This synthesized event data is then processed into a novel event image representation called Pseudo-Frames. Second, we mitigate the shortage of Natural Language (NL)-described datasets by employing the Visual-Language (VL) image-captioning module, comprising BLIP-2 and GPT-4, to generate captions for eight VOT benchmarks *** propose a multi-modal Visual-Language Object Tracking (VLOT) framework named ELTrack, which integrates RGB, event, and Natural Language Processing (NLP) modalities to enhance tracking performance. Our framework includes a simple superimpose fusion module that combines RGB frames with the proposed Pseudo-Frames, along with our VL image-captioning module to provide NL descriptions for the given sequences. Extensive experiments on our proposed framework demonstrate its effectiveness in addressing VOT challenges and achieving state-of-the-art (SOTA) performance across eight tracking *** datasets, NL descriptions, and source code associated with this work will be made available at: \url{https://***/HamadYA/ELTrack-Correlating-Events-and-Language-for

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

Integrating Existing Knowledge to Accelerate Buildings Renovation Rates in Europe 9th

Integrating Existing Knowledge to Accelerate Buildings Renov...

引用

9th International Conference on Decision Support System Technology, ICDSST 2023

作者： Karakosta, Charikleia Mylona, Zoi Papathanasiou, Jason Psarras, John Decision Support Systems Laboratory School of Electrical and Computer Engineering National Technical University of Athens 9 Iroon Polytechniou str. Zografou Athens15780 Greece HOLISTIC IKE 507 Mesogion Av.Ag. Paraskevi Athens15343 Greece Department of Business Administration University of Macedonia 156 Egnatia Street Thessaloniki54636 Greece

ISBN: (纸本)9783031325335

Nowadays, boosting the implementation of energy efficiency measures in buildings and subsequently, mainstreaming energy efficiency financing is of paramount importance for the European Union towards achieving its goal of carbon-neutrality by 2050. Unfortunately, statistics have shown that a lot of effort is needed to achieve the Europe’s targets, since energy efficiency is not yet considered as an attractive investment by the financial sector. The lack of expertise and knowledge, as well as the different perspective of project developers and financing institutions are some indicative challenges that have to be overcome. Specific to energy efficiency in buildings this is reflected by the current insufficient trends observed in the renovation rates of buildings, which reveal the urgent need for action since this is the largest consumer of energy in Europe. Furthermore, a combination of public and private funding through innovative financing instruments is required to overcome current barriers that prevent mobilization of necessary investments. The aim of this paper is to set up a role-based methodological approach for the deployment of an integrated matchmaking mechanism on an ICT platform to boost energy efficiency investments in an easy-access and trust-worthy way. The methodology envisages to follow a multidisciplinary perspective which takes into account the interactions between various key factors, such as stakeholders and barriers, so as to facilitate the complex set of decision-making actions for building renovation. The core of concept centres around the definition of the roles of the potential users of a big data for buildings platform, their interdependency and requirements with the ultimate purpose of accelerating renovation rates. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

Convergence Condition of Simplified Information Geometry Approach for Massive MIMO-OFDM Channel Estimation

Convergence Condition of Simplified Information Geometry App...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： Mingrui Fan Jiyuan Yang Yan Chen An-An Lu Xiqi Gao Xiang-Gen Xia Dirk Slock National Mobile Communications Research Laboratory Southeast University Nanjing China Purple Mountain Laboratories Nanjing China Department of Electrical and Computer Engineering University of Delaware Newark DE USA Department of Communication Systems EURECOM Biot France

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

In this paper, we prove the convergence of the simplified information geometry approach (SIGA), which was proposed for massive MIMO-OFDM channel estimation. For a general Bayesian inference problem, we first show that the iteration of the common second-order natural parameter (SONP) is separated from that of the common first-order natural parameter (FONP). Hence, the convergence of the common SONP can be checked independently. We show that with the initialization satisfying a specific but large range, the common SONP is convergent regardless of the value of the damping factor. For the common FONP, we establish a sufficient condition of its convergence and prove that the convergence of the common FONP relies on the spectral radius of a particular matrix related to the damping factor. We give the range of the damping factor that guarantees the convergence in the worst case. Further, we determine the range of the damping factor for massive MIMO-OFDM channel estimation by using the specific properties of the measurement matrices. Simulation results are provided to confirm the theoretical results.

关键词： Damping Sufficient conditions Information geometry Vehicular and wireless technologies Simulation Channel estimation Bayes methods

来源：评论

学校读者我要写书评

暂无评论

Deep Neural Network Enhanced Chip-on-board Hybrid-Packaged Photonic-electrical Silicon Transceiver for High-speed Optical Interconnects

Deep Neural Network Enhanced Chip-on-board Hybrid-Packaged P...

引用

CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Qin, Jun Yang, Qipeng Han, Changhao Zhou, Yan Zhang, Yunhao Wu, Yichen Sun, Yu Lu, Junde Liu, Siming Li, Yueqin Sun, Jian Min, Miao Hu, Weiwei He, Zhixue Wang, Lei Yu, Shaohua Shu, Haowen Wang, Xingjun Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science and Technology University Beijing100192 China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing100871 China Department of Electrical and Computer Engineering University of California Santa BarbaraCA93106 United States Peking University Yangtze Delta Institute of Optoelectronics Nantong226010 China Peng Cheng Laboratory Shenzhen518055 China State Key Laboratory of Information Photonics and Optical Communications BUPT Beijing100876 China

We explore implementing a multilevel deep neural network to enhance the performance of a 4-channel photonic-electrical hybrid-packaged silicon transceiver. Stable transmission and reception of 150 Gbps/λ PAM4 signals... 详细信息

关键词： Optical interconnects

来源：评论

学校读者我要写书评

暂无评论

Deep Neural Network Enhanced Chip-on-board Hybrid-Packaged Photonic-electrical Silicon Transceiver for High-speed Optical Interconnects

Deep Neural Network Enhanced Chip-on-board Hybrid-Packaged P...

引用

2024 Conference on Lasers and Electro-Optics, CLEO 2024

ISBN: (纸本)9781957171395

关键词： Optical interconnects

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：