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Timing Behavior Characterization of Critical real-time systems through Hybrid Timing Analysis 7

Timing Behavior Characterization of Critical Real-Time Syste...

引用

7th international conference on System Reliability and Safety, ICSRS 2023

作者： Barone, Salvatore Casola, Valentina Torca, Salvatore Della Lombardi, Daniele University of Naples Federico Ii Department of Electrical Engineering and Information Technologies Naples80125 Italy Univeristy of Bergamo Department of Management Information and Production Engineering Dalmine24044 Italy

ISBN: (纸本)9798350306057

The spread of computing-systems, especially the realtime embedded ones, is rapidly growing in the last years, since they find usage in numerous fields of application, including, but not limited to, industry process, critical infrastructures, transportation systems, as so forth. Indeed, in these fields, precise time-constraints hold;hence, tasks need to be correct from both the functional and temporal perspectives. As for the latter, timing behavior has to be characterized, that is usually done by exploiting either static or dynamic analysis techniques, which leverage estimations based on either a model or the actual system. In this paper, we foster an automated hybrid approach that allows characterizing the timing behavior of systems while introducing any alteration, i.e., relying on instruction-level tracing rather than code instrumentation for profiling purposes. Our approach is sensitive to the execution-context, - e.g., cache misses - and it allows re-using results from the development processes - e.g., unit tests. We considered a complex realtime application from the railway domain as a case study to evaluate our approach, empirically proving that it can provide a faithful characterization of systems in terms of worst-case execution time. © 2023 ieee.

关键词： real time systems

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The Internet of Things (IoT) Contribution to Natural Disaster Management: Review 20

The Internet of Things (IoT) Contribution to Natural Disaste...

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20th ACS/ieee international conference on Computer systems and applications (AICCSA)

作者： Goyal, Dinesh Sharma, Aditya Garg, Kamal Deep Sharma, Bhisham Ben Dhaou, Imed Chitkara Univ Inst Engn & Technol Rajpura Punjab India Dar Al Hekma Univ Hekma Sch Engn Comp & Design Dept Comp Sci Jeddah Saudi Arabia

ISBN: (纸本)9798350319439

Natural Disaster provide serious problems for communities all over the world, with severe effects on the environment, infrastructure, and human lives. Effective disaster management solutions are increasingly important as the frequency and severity of these events rise to limit losses and ensure quick responses. A creative and promising approach to improving disaster management skills is the introduction of the Internet of Things (IoT). A brief description of the use of IoT in managing natural disasters is provided in this abstract. With the help of several networked sensors and devices, the Internet of Things (IoT) enables real-time data gathering, processing, and transmission. Utilizing this technology can result in preemptive and more efficient disaster response plans. Although there is great promise for IoT integration in disaster management, there are also issues with privacy of data, protection, and interoperability. For Internet of Things (IoT) technologies in disaster management to be successfully implemented and accepted, these problems must be addressed. This offers a brief glimpse of the revolutionary potential of IoT in tackling the intricate problems of catastrophe management.

关键词： Internet of Things (IoT) Disaster Management Early Warning systems IoT Sensors Remote Sensing GPS Tracking

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3DS: An Efficient DPDK-based Data Distribution Service for Distributed real-time applications 24

3DS: An Efficient DPDK-based Data Distribution Service for D...

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24th ieee international conference on High Performance computing and Communications, 8th ieee international conference on Data Science and systems, 20th ieee international conference on Smart City and 8th ieee international conference on Dependability in Sensor, Cloud and Big Data systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Xu, Tianyu Chen, Xianzhang Wu, Changze Wang, Jiapin Zheng, Rongwei Liu, Duo Tan, Yujuan Ren, Ao Li, Jian College of Computer Science Chongqing University Chongqing China School of Big Data and Software Engineering Chongqing University Chongqing China School of Electrical Engineering Chongqing University Chongqing China

ISBN: (纸本)9798350319934

Data Distribution Service (DDS) is a widely-used middleware for data transmission in distributed real-time applications, such as autonomous vehicles and robotics. However, the communication of existing DDS middlewares generally relies on the network stacks of the operating system, which brings long latency to the real-time applications. In this paper, we propose a DPDK-based DDS, dubbed 3DS, to improve the performance of communication of DDS middlewares. First, 3DS reduces the latency of communication between distributed real-time applications by avoiding the latency of kernel. Second, 3DS reduces the overhead of dynamic memory allocation and deallocation by a reserved memory pool. Finally, 3DS adopts a thread-exclusive CPU model to reduce the resource contention between threads. We implement and evaluate 3DS on real systems running Linux. The experimental results show that 3DS reduces 44% of the communication latency over FastDDS, which is the state-of-the-art DDS middleware used by ROS2. Moreover, the throughput of data transfer in 3DS can be 1.51 times that of FastDDS. © 2022 ieee.

关键词： Data transfer

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A 181 μW real-time 3-D Hand-Gesture Recognition System for Edge applications 4

A 181 μW Real-Time 3-D Hand-Gesture Recognition System for ...

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ieee international conference on Artificial Intelligence Circuits and systems (AICAS) - Intelligent Technology in the Post-Pandemic Era

作者： Lu, Yuncheng Li, Zehao Zhang, Xin Kim, Tony Tae-Hyoung Nanyang Technol Univ Sch Elect & Elect Engn Ctr Integrated Circuits & Syst Singapore Singapore

ISBN: (数字)9781665409964

ISBN: (纸本)9781665409964

This demonstration presents an ultra-low-power real-time 3-D hand gesture recognition system for edge scenarios. The rotation-resistant features are extracted through bi-directional convolution, and the gestures are classified based on an iteration-free feature clustering scheme. The computing-intensive units for gesture recognition are adaptively gated according to the input data patterns for power saving. The proposed system can recognize 9 static and 20 dynamic hand gestures with an average accuracy of 94.4% and 98.6%, respectively. Besides, it can track the fingertips in real-time. The measurement result shows the prototype chip achieves the lowest power of 181 mu W at 0.6 V and 25 MHz.

关键词： low-power high accuracy 3-D hand gesture recognition

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Developing IoT-based Smart Health Monitoring systems using Design Patterns 20

Developing IoT-based Smart Health Monitoring Systems using D...

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20th ACS/ieee international conference on Computer systems and applications (AICCSA)

作者： Ben Hassine, Mariem Tounsi, Imen Kacem, Mohamed Hadj Univ Sfax ReDCAD Lab ENIS Sfax Tunisia

ISBN: (纸本)9798350319439

The Internet of Things (IoT) is a rapidly growing network of interconnected devices, ranging from sensors and actuators to smart appliances and wearable devices. The proliferation of these connected devices generates vast amounts of data and enables a broad range of applications and services, adding to the complexity of IoT development systems. To address this complexity, careful consideration of design patterns and modeling techniques are necessary to ensure that IoT systems are scalable, flexible, and maintainable. In the healthcare industry, IoT-based systems is being developed to improve patient care and outcomes while also managing costs. However, these systems pose significant challenges because IoT-based monitoring of health parameters demands meticulous attention to detail. Even slight inaccuracies in the collected data could have severe consequences for patient diagnosis and treatment. Additionally, any system failures or disruptions could delay crucial interventions and significantly impact patient outcomes. Consequently, it is imperative to carefully consider the design and implementation of IoT-based healthcare systems to guarantee accurate data collection and timely interventions. In this paper, we present the approach involved in developing IoT-based smart health monitoring systems to collect and analyze patient data related to their health and wellbeing. The focus of this research is to identify and model the best practices for developing scalable and flexible IoT-based healthcare systems that address the challenges of remote patient monitoring, including the need for continuous monitoring, real-time feedback, and early detection of health issues.

关键词： Internet of Things architecture Design Patterns E-health Pattern modeling

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Supercapacitor Digital Twin Management System Based on Cloud Environment 23

Supercapacitor Digital Twin Management System Based on Cloud...

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23rd ieee international conference on High Performance computing and Communications, 7th ieee international conference on Data Science and systems, 19th ieee international conference on Smart City and 7th ieee international conference on Dependability in Sensor, Cloud and Big Data systems and applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Yang, Yingze Zhao, Qinxian Gao, Dianzhu Rong, Jieqi Fan, Yunsheng Li, Heng Peng, Jun School of Computer Science and Engineering Central South University Changsha410083 China School of Automation Central South University Changsha410083 China Hunan Engineering Laboratory of Rail Vehicles Braking Technology Changsha410083 China

ISBN: (纸本)9781665494571

With the continuous promotion of the green transportation concept, supercapacitors have gained popularity for their excellent charging and discharging characteristics. However, the unreasonable management of supercapacitor will lead to poor safety and reliability of the supercapacitor system. Aiming at this problem, a supercapacitor cloud management system based on the digital twin is proposed in this paper, which improves the computing power and data storage capacity through cloud computing for the whole life cycle state monitoring of supercapacitors. Firstly, the mathematical modeling of the supercapacitor system is carried out, and the state parameters during the charging and discharging of the supercapacitor are obtained in real-time at the physical layer and uploaded to the data interaction network. Secondly, in the network layer, all data related to the supercapacitor are measured and transmitted to the cloud through IoT, and a digital twin cloud model of the supercapacitor management system is established to evaluate the usage status of the supercapacitor by using the real-time data in the data interaction network. Finally, the supercapacitor charging and discharging control strategy is adjusted in real-time based on the state evaluation results at the control layer and given a visualization window visible to users. The application of the supercapacitor system in the digital twin is explored by developing a parameter estimation algorithm suitable for cloud computing. The experimental results verify the feasibility and practicality of the proposed supercapacitor cloud management system. © 2021 ieee.

关键词： Cloud computing Smart cities Supercapacitors real-time systems Data models Digital twins Topology

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Design and Implementation of Memristive Hyperchaotic Image Encryption Experimental Platform Based on embedded Linux System

Design and Implementation of Memristive Hyperchaotic Image E...

引用

2023 ieee international conference on Memristive computing and applications, ICMCA 2023

作者： Chen, Xinhui Wang, Xiaoyuan Zhang, Xinrui Liu, Zijian Ha, Congyin Wu, Xianming School of Electronics and Information Hangzhou Dianzi University Hangzhou China College of Information Engineering Jinhua Polytechnic Jinhua China College of Information Engineering Beihang University Beijing China School of Mechanical & Electrical Engineering Guizhou Normal University Guiyang China

ISBN: (纸本)9798350316230

In this manuscript, an image encryption experimental platform based on hyperchaotic pseudo-random sequence is developed based on Linux operating system. The platform utilizes hyperchaotic synchronization technology for secure key transmission between encryption and decryption terminals. Firstly, a hyperchaotic system based on a tri-valued memristor is proposed. Then, the software of client and server are designed to realize the interactive transmission of images under different systems. Simultaneously, a network channel is constructed for file transmission. After that, the graphical user interface is designed based on QT tool, which ensures that the image encryption software possesses satisfactory visual effect and operability. Finally, encryption and decryption functions are developed in Linux system utilizing OpenCV library functions for image data handling. The results demonstrate that the platform effectively performs both image encryption and decryption functions, enhancing the security of embedded device information. © 2023 ieee.

关键词： Memristors

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OpTree: An Efficient Algorithm for All-gather Operation in Optical Interconnect systems

OpTree: An Efficient Algorithm for All-gather Operation in O...

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ieee international conference on Communications (ieee ICC)

作者： Dai, Fei Chen, Yawen Huang, Zhiyi Zhang, Haibo Univ Otago Dept Comp Sci Dunedin New Zealand

ISBN: (纸本)9781538674628

All-gather collective communication is one of the most important communication primitives in parallel and distributed computation, which plays an essential role in many high performance computing (HPC) applications such as distributed Deep Learning (DL) with model and hybrid parallelisms. To solve the communication bottleneck of All-gather, optical interconnection network can provide unprecedented high bandwidth and reliability for data transfer among the distributed nodes. However, most traditional All-gather algorithms are designed for electrical interconnection, which cannot fit well for optical interconnect systems, resulting in poor performance. This paper proposes an efficient scheme, called OpTree, for All-gather operation on optical interconnect systems. OpTree derives an optimal m-ary tree corresponding to the optimal number of communication stages, which achieves the minimum communication time. We further analyze and compare the communication steps of OpTree with existing All-gather algorithms. Theoretical results exhibit that OpTree requires much less number of communication steps than existing All-gather algorithms on optical interconnect systems. Simulation results show that OpTree can reduce communication time by 72.21%, 94.30%, and 88.58% compared to three existing All-gather schemes WRHT, Ring, and NE, respectively.

关键词： Optical interconnects All-gather communication WDM

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A Self-Powered Sensing System with embedded TinyML for Anomaly Detection 3

A Self-Powered Sensing System with Embedded TinyML for Anoma...

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3rd ieee international conference on Industrial Electronics for Sustainable Energy systems, IESES 2023

作者： Chen, Zijie Gao, Yiming Liang, Junrui School of Information Science and Technology ShanghaiTech University Shanghai201210 China

ISBN: (纸本)9798350324754

In the coming Industry 4.0 era, IoT (Internet of Things) technology plays a more and more critical role. Anomaly detection is one of the essential applications for ensuring safe manufacturing, living, etc. It equips the machine with intelligence for perceiving its situation in real-time to prevent disastrous breakdown. Such monitoring systems were usually based on commercial inertial measurement units (IMU) and artificial intelligence (AI) algorithms that run on resource-rich, power-hungry servers, causing a certain amount of energy for sensing and data transmitting. In this paper, we introduce a novel self-powered sensing system with tiny machine learning (Tiny ML) technique for anomaly detection. A lightweight piezoelectric self-powered sensor (SPS) is utilized to substitute the IMU. The system runs on a low-cost embedded system, realizing the low-power in-situ inferring. A rich dataset has been collected on a vibration platform and analyzed by six well-known machine-learning models. A compressed deep neuron network (DNN) with three hidden layers achieves an accuracy of 97.6 % given only 8-point normalized SPS data. The TinyML model is then deployed on embedded systems for on-device inferring and condition-based monitoring. Power measurement is conducted to compare the systems based on an IMU and an SPS. It has shown that the proposed self-powered sensing approach can save up to 66.74% of energy. The system provides a valuable reference for realizing pervasive sensing and ubiquitous AI. © 2023 ieee.

关键词： Anomaly detection

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CommonRoad-Reach: A Toolbox for Reachability Analysis of Automated Vehicles 25

CommonRoad-Reach: A Toolbox for Reachability Analysis of Aut...

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ieee 25th international conference on Intelligent Transportation systems (ITSC)

作者： Liu, Edmond Irani Wuersching, Gerald Klischat, Moritz Althoff, Matthias Tech Univ Munich Dept Informat D-85748 Garching Germany

ISBN: (数字)9781665468800

ISBN: (纸本)9781665468800

In recent years, reachability analysis has gained considerable popularity in motion planning and safeguarding of automated vehicles (AVs). While existing tools for reachability analysis mainly focus on general-purpose algorithms for formal verification of dynamical systems, a toolbox tailored to AVspecific applications is not yet available. In this study, we present CommonRoad-Reach, which is a toolbox that integrates different methods for computing reachable sets and extracting driving corridors for AVs in dynamic traffic scenarios. Our toolbox provides a Python interface and an efficient C++ implementation for real-time applications. The toolbox is integrated within the CommonRoad benchmark suite and is available at ***.

关键词： Heuristic algorithms Dynamics Benchmark testing real-time systems Planning Vehicle dynamics Reachability analysis

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