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44th IEEE Real-Time Systems Symposium, RTSS 2023

作者： Li, Zonghong Xie, Guoqi Ma, Wenhong Xiao, Xiongren Xie, Yong Ren, Wei Chang, Wanli College of Computer Science and Electronic Engineering Hunan University Key Laboratory for Embedded and Network Computing of Hunan Province China Research Institute of Hunan University Chongqing China Nanjing University of Posts and Telecommunications China Huawei Technologies China

ISBN: (纸本)9798350328578

Virtual machines (VMs) have been increasingly deployed in real-time systems to enhance heterogeneous resource sharing. Despite being isolated for security and prevention of failure propagation, VMs need to communicate with each other to complete certain tasks jointly. A real-time inter-VM communication framework has been proposed based on VirtIO, which is in essence a mechanism of message passing with high latency and low scalability on data amount. In contrary, IVSHMEM implements inter-VM communication with shared memory, which is generally fast and large in throughput. Unfortunately, IVSHMEM does not resolve resource contention between flows and hence cannot be applied in real-time scenarios. In this work, we propose a real-time inter-VM communication framework RTISM built upon shared memory and IVSHMEM. RTISM provides priority-based scheduling and supports mixed-criticality flows. Worst-Case Response Time (WCRT) analysis is reported to bound the end-to-end communication delay and a Limited Priority Assignment (LPA) algorithm is developed to enhance schedulability. Experimental evaluation shows that (i) RTISM has about 4 times higher throughput than the VirtIO-based inter-VM communication framework;(ii) LPA improves schedulability by over 25% compared to the state-of-the-art;(iii) WCRT produces a tight bound. © 2023 IEEE.

关键词： Real time systems

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Holistic WCRT Analysis for Global Fixed-Priority Preemptive Multiprocessor Scheduling 23

Holistic WCRT Analysis for Global Fixed-Priority Preemptive ...

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Proceedings of the 60th Annual ACM/IEEE Design Automation Conference

作者： Guoqi Xie Chenglai Xiong Wei Wu Renfa Li Wanli Chang Key Laboratory for Embedded and Network Computing of Hunan Province College of Computer Science and Electronic Engineering Hunan University China.

ISBN: (纸本)9798350323481

Many embedded applications demand both resource efficiency and timing guarantee. However, resource sharing naturally complicates the analysis that extracts the worst-case scenario out of contention. Global Fixed-Priority (GFP) preemptive multiprocessor scheduling is one of the mainstream strategies to resolve contention on computational resources. It allows jobs of the same task to be executed on different processors, hence potentially enabling better parallelism and more efficient resource utilization. Unfortunately, its worst-case response time (WCRT) analysis is challenging. Existing approaches divide a high-priority task into three workloads, namely, carry-in workload, body workload, and carry-out workload, trying to optimize them individually. In this work, we propose a holistic WCRT analysis for GFP preemptive multiprocessor scheduling, where a task is no longer divided. Specifically, (i) we establish the tight interference scenario for the task being analyzed to find the most interfering high-priority jobs in any time interval; (ii) we obtain the starting released instant of each high-priority task's first job to determine the maximum interference from high-priority tasks' first jobs to the task being analyzed; (iii) we build the worst-case tight interference scenario for the task being analyzed by combining the tight interference scenario and the starting released instants; (iv) we prove that the WCRT of the task being analyzed can be decided by the worst-case tight interference scenario. Evaluation on schedulability shows that our proposed analysis achieves 4.2%-8.6% higher acceptance ratio in randomly generated data sets than the state-of-the-art workload division approaches.

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An Efficient Three-Factor Privacy-Preserving Authentication and key Agreement Protocol for Vehicular Ad-Hoc network

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China Communications 2021年第12期18卷 315-331页

作者： Tao Xu Cheng Xu Zisang Xu School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Key Laboratory for Embedded and Network Computing of Hunan Province Changsha 410082China

As an indispensable part of the Intelli-gent Transportation System(ITS),the vehicular ad-hoc network(VANET)has attracted widespread atten-tion from academia and *** order to ensure the security of VANET,vehicles need to be authen-ticated before accessing the *** existing authentication protocols in VANET adopt the Trusted Authority(TA)with centralized structure which is re-sponsible for the authentication tasks of all ***,the large-scale network consume a lot of computing resources,which leads to unacceptable de-lay in message transmission in *** reducing the computational cost of TA,an efficient three-factor privacy-preserving authentication and key agreement protocol was proposed in our *** from before,the RoadSide Unit(RSU)no longer acts as an intermediate node but is responsible for assisting user authentication,which lead to the computational cost of TA is very *** formal and informal analysis,our protocol demonstrates excellent ***-pared with previous studies,our work emerges advan-tages and superiorities in the following aspects:com-putational cost,communication cost,security proper-ties and functions,message loss ratio,and message *** data and evidence indicate that our protocol is an ideal choice for large-scale VANET.

关键词： authentication vehicular ad-hoc network security three-factor

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A recent survey on controllable text generation: A causal perspective

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Fundamental Research 2024年第3期5卷 1194-1203页

作者： Wang, Junli Zhang, Chenyang Zhang, Dongyu Tong, Haibo Yan, Chungang Jiang, Changjun Key Laboratory of Embedded System and Service Computing (Tongji University) Ministry of Education Shanghai 201804 China National (Province-Ministry Joint) Collaborative Innovation Center for Financial Network Security Tongji University Shanghai 201804 China

As an important subject of natural language generation, Controllable Text Generation (CTG) focuses on integrating additional constraints and controls while generating texts and has attracted a lot of attention. Existing controllable text generation approaches mainly capture the statistical association implied within training texts, but generated texts lack causality consideration. This paper intends to review recent CTG approaches from a causal perspective. Firstly, according to previous research on basic types of CTG models, it is discovered that their essence is to obtain the association, and then four kinds of challenges caused by absence of causality are introduced. Next, this paper reviews the improvements to address these challenges from four aspects, namely representation disentanglement, causal inference, knowledge enhancement and multi-aspect CTG respectively. Additionally, this paper inspects existing evaluations of CTG, especially evaluations for causality of CTG. Finally, this review discusses some future research directions for the causality improvement of CTG and makes a conclusion. © 2024

关键词： Causal inference Causality Controllable text generation Knowledge enhancement Representation disentanglement

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A Rolling Bearing Fault Diagnosis Method Using Multi-Sensor Data and Periodic Sampling

A Rolling Bearing Fault Diagnosis Method Using Multi-Sensor ...

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2022 IEEE International Conference on Multimedia and Expo, ICME 2022

作者： Zheng, Jianbo Yang, Chao Zheng, Fangrong Jiang, Bin College of Computer Science and Electronic Engineering Hunan University China Key Laboratory for Embedded and Network Computing of Hunan Province China School of Computational Science and Electronics Hunan Institute of Engineering China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

In recent years, bearing fault diagnosis based on deep learning has gradually become the mainstream. However, the existing studies still have some defects, such as unreasonable sampling and incomplete utilization of bearing data, limiting the further improvement of the performance of the fault diagnosis model. This paper proposes a fault diagnosis method using multi-sensor data and periodic sampling to solve the problems above. First, the vibration data of different bearing positions are fused into multi-channel fusion data to improve the defect of insufficient data utilization. Second, based on the sampling length and sampling stride, periodic sampling is carried out for the fusion data to solve the problem of unreasonable sampling. Third, the traditional convolutional neural network is adjusted to extract more detailed fault features and obtain the best recognition effect. Finally, the experimental results verify the effectiveness of the proposed method. © 2022 IEEE.

关键词： Failure analysis

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Brief Industry Paper: Response Time Evaluation of Cross-Domain Communication in CAN-FD and TSN

Brief Industry Paper: Response Time Evaluation of Cross-Doma...

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Real-Time Systems Symposium (RTSS)

作者： Wenhong Ma Xiaoyi Huang Dongsheng Wei Renfa Li Yunfei Zhang Guoqi Xie Wanli Chang Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University China Tencent Future Network Lab Tencent Corporation China

With the advancement of intelligence and networked automotive, the domain-centralized architecture, which employs time sensitive networking (TSN) as the inter-domain backbone network and control area network with flexible data rate (CAN-FD) as the intra-domain network, has garnered significant attention. However, cross-domain end-to-end communication involves multiple components, and significant disparities between TSN and CAN-FD render response time analysis within domain-centralized architecture for mixed-critical traffic exceptionally complex. In this paper, we develop a cross-domain with TSN and CAN-FD end-to-end response time evaluation tool, which analyzes the response time of mixed-critical traffic under different design options segment by segment. We specifically analyze the waiting times of different messages in the domain control unit when faced with the design options of one-to-one and multi-to-one conversion of CAN-FD and TSN frames. The proposed evaluation tool can be easily extended to different design options to support more application scenarios. Theoretical computational analysis and real hardware measurements show the effectiveness of our tool.

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Holistic WCRT Analysis for Global Fixed-Priority Preemptive Multiprocessor Scheduling

Holistic WCRT Analysis for Global Fixed-Priority Preemptive ...

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Design Automation Conference

Many embedded applications demand both resource efficiency and timing guarantee. However, resource sharing naturally complicates the analysis that extracts the worst-case scenario out of contention. Global Fixed-Priority (GFP) preemptive multiprocessor scheduling is one of the mainstream strategies to resolve contention on computational resources. It allows jobs of the same task to be executed on different processors, hence potentially enabling better parallelism and more efficient resource utilization. Unfortunately, its worst-case response time (WCRT) analysis is challenging. Existing approaches divide a high-priority task into three workloads, namely, carry-in workload, body workload, and carry-out workload, trying to optimize them individually. In this work, we propose a holistic WCRT analysis for GFP preemptive multiprocessor scheduling, where a task is no longer divided. Specifically, (i) we establish the tight interference scenario for the task being analyzed to find the most interfering high-priority jobs in any time interval; (ii) we obtain the starting released instant of each high-priority task’s first job to determine the maximum interference from high-priority tasks’ first jobs to the task being analyzed; (iii) we build the worst-case tight interference scenario for the task being analyzed by combining the tight interference scenario and the starting released instants; (iv) we prove that the WCRT of the task being analyzed can be decided by the worst-case tight interference scenario. Evaluation on schedulability shows that our proposed analysis achieves 4.2%-8.6% higher acceptance ratio in randomly generated data sets than the state-of-the-art workload division approaches.

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Infra-YOLO: Efficient Neural network Structure with Model Compression for Real-Time Infrared Small Object Detection

arXiv

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arXiv 2024年

作者： Chen, Zhonglin Geng, Anyu Jiang, Jianan Lu, Jiwu Wu, Di The College of Electrical and Information Engineering Hunan University Hunan Changsha410082 China The Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University Hunan Changsha410082 China

Although convolutional neural networks have made outstanding achievements in visible light target detection, there are still many challenges in infrared small object detection because of the low signal-to-noise ratio, incomplete object structure, and a lack of reliable infrared small object dataset. To resolve limitations of the infrared small object dataset, a new dataset named InfraTiny was constructed, and more than 85% bounding box is less than 32x32 pixels (3218 images and a total of 20,893 bounding boxes). A multi-scale attention mechanism module (MSAM) and a Feature Fusion Augmentation Pyramid Module (FFAFPM) were proposed and deployed onto embedded devices. The MSAM enables the network to obtain scale perception information by acquiring different receptive fields, while the background noise information is suppressed to enhance feature extraction ability. The proposed FFAFPM can enrich semantic information, and enhance the fusion of shallow feature and deep feature, thus false positive results have been significantly reduced. By integrating the proposed methods into the YOLO model, which is named Infra-YOLO, infrared small object detection performance has been improved. Compared to yolov3, mAP@0.5 has been improved by 2.7%;and compared to yolov4, that by 2.5% on the InfraTiny dataset. The proposed Infra-YOLO was also transferred onto the embedded device in the unmanned aerial vehicle (UAV) for real application scenarios, where the channel pruning method is adopted to reduce FLOPs and to achieve a tradeoff between speed and accuracy. Even if the parameters of Infra-YOLO are reduced by 88% with the pruning method, a gain of 0.7% is still achieved on mAP@0.5 compared to yolov3, and a gain of 0.5% compared to yolov4. Experimental results show that the proposed MSAM and FFAFPM method can improve infrared small object detection performance compared with the previous benchmark method. © 2024, CC BY-NC-ND.

关键词： Convolutional neural networks

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Fault Tolerance in Time-Sensitive networking with Mixed-Critical Traffic 23

Fault Tolerance in Time-Sensitive Networking with Mixed-Crit...

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Proceedings of the 60th Annual ACM/IEEE Design Automation Conference

作者： Wenhong Ma Xiangzhen Xiao Guoqi Xie Nan Guan Yu Jiang Wanli Chang Key Laboratory for Embedded and Network Computing of Hunan Province College of Computer Science and Electronic Engineering Hunan University City University of Hong Kong Tsinghua University China

ISBN: (纸本)9798350323481

As an Ethernet-based communication protocol with timing determinism, TSN (time-sensitive networking) has become a well-recognized promising in-vehicle network solution for increasingly automated automobiles. To satisfy the reliability requirement of safety-critical applications, existing works towards fault-tolerant TSN trade too much bandwidth for redundancy, limiting their scope of applicability. Targeting mixed-critical traffic, which is widely found in practice, we define a shared fault-tolerant segment that is compatible with the TSN standard. It serves the critical flows when faults occur, to improve their reliability and serves the non-critical flows when otherwise, to improve their quality of service (QoS). On top of this, we propose a space-time redundancy scheduling algorithm, aiming to make the most efficient use of bandwidth, i.e., to fulfill both the reliability as well as hard real-time requirements, and maximize the QoS with the least bandwidth. In essence, we formulate a bi-objective design space exploration problem with hundreds of thousands of decision variables and solve it with customized heuristics. Experimental results show that compared to the state-of-the-art methods, our reported work increases the number of critical flows that can be accommodated on a resource-constrained network by 3 to 4 times, and achieve the highest QoS with an average reduction of 60.3% in bandwidth. As the first work along sharing of bandwidth between mixed-critical traffic in fault-tolerant TSN, this idea can be further pursued towards higher efficiency and may be applied in general autonomous systems.

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LIDS: A Lightweight Intrusion Detection System for Controller Area network

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IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 2025年

作者： Yu, Zhangwei Liu, Yan Li, Renfa Chang, Wanli Hunan University Key Laboratory for Embedded and Network Computing of Hunan Province College of Computer Science and Electronic Engineering Changsha410082 China Research Institute of Hunan University in Chongqing Research and Innovation Center for Convergence of Automobile and Cyberspace Chongqing401120 China

Controller Area network (CAN) is widely adopted in automobiles and susceptible to cyber attacks with the development of intelligent connected vehicles. While neural networks have demonstrated high accuracy in detection of such attacks, they consume a large amount of resources, hence unsuitable to be directly used for the automotive domain. In this work, we propose LIDS, a lightweight intrusion detection system for CAN. It first filters out DoS (Denial of Service) and Fuzzy attacks through list screening, following which, a Multi-Layer Perceptron (MLP) model is deployed to predict Impersonation attacks. Leveraging this combination, the detection accuracy is kept and the resources required are significantly reduced. LIDS is able to run on small hardware with 520KB memory and CPU of 240MHz. Its power consumption is one order of magnitude lower than the existing works, thus an excellent candidate for protection of CAN in automobiles. © 1982-2012 IEEE.

关键词： Automobiles

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