检索结果-内蒙古大学图书馆

ieee international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Tobias Betz Long Wen Fengjunjie Pan Gemb Kaljavesi Alexander Zuepke Andrea Bastoni Marco Caccamo Alois Knoll Johannes Betz Technical University of Munich Germany

ISBN: (数字)9798350387957

ISBN: (纸本)9798350387964

the automotive industry is transitioning from traditional ECU-based systems to software-defined vehicles. A central role of this revolution is played by containers, lightweight virtualization technologies that enable the flexible consolidation of complex software applications on a common hardware platform. Despite their widespread adoption, the impact of containerization on fundamental real-time metrics such as end-to-end latency, communication jitter, as well as memory and CPU utilization has remained virtually unexplored. this paper presents a microservice architecture for a real-world autonomous driving application where containers isolate each service. Our comprehensive evaluation shows the benefits in terms of end-to-end latency of such a solution even over standard bare-Linux deployments. Specifically, in the case of the presented microservice architecture, the mean end-to-end latency can be improved by 5–8%. Also, the maximum latencies were significantly reduced using container deployment.

关键词： Measurement Operating systems Microservice architectures Computer architecture Containers real-time systems Software Virtualization Autonomous vehicles Standards

来源：评论

学校读者我要写书评

暂无评论

LEM: a Tool for Large-Scale Workflow Control in Edge-Based Industry 5.0 applications 19

LEM: a Tool for Large-Scale Workflow Control in Edge-Based I...

引用

19th Annual international conference on Distributed computing in Smart systems and the Internet of things, DCOSS-IoT 2023

作者： Reis, Rui Santos, Pedro M. Sousa, Mario J. Martins, Nuno Sousa, Joana Almeida, Luis Universidade Do Porto Faculdade de Engenharia Portugal Portugal Cister Research Center in Real-Time and Embedded Computing Systems Portugal

ISBN: (纸本)9798350346497

Edge computing is poised to greatly boost Industry 5.0 by providing a computing substrate that can run highly specialized applications with minimal latency, reducing the requirements on computational resources at the end-user and allowing the sharing of resources between multiple end-users. the intended services and workflows need to be designed, configured and deployed at target edge devices, and during operation their status needs to be monitored. there are several industrial frameworks that provide such functionalities, but often there is little support to execute them simultaneously over many target devices. In this paper we present the LEM tool, a tool that enables the management (monitor, configure, deploy) of workflows in a large number of edge devices. the tool connects to existing industrial frameworks to provide these functionalities, abstracting the low level configuration aspects of each framework and enabling simultaneous configuration of multiple devices, a feature that many frameworks do not support. the tool offers a web-based GUI that allows the infrastructure manager to conveniently check the status of all devices and flows running in each device, deploy new flows on selected devices, and start and stop flows. Experimental measurements show residual response time overhead as the number of devices increases. © 2023 ieee.

关键词： edge Industry5.0 Node-RED workflow

来源：评论

学校读者我要写书评

暂无评论

Visualization System Using Virtual reality for Work Improvement in Small and Medium Manufacturing Industries

Visualization System Using Virtual Reality for Work Improvem...

引用

ieee international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Shogo Ogihara Tetsuro Kato Takafumi Kawasaki Yuki Okura Takeshi Iwamoto Electrical and Computer Engineering Graduate School of Engineering Toyama Prefectural University Toyama Japan IoTry Inc. Toyama Japan Department of Information Systems Engineering Toyama Prefectural University Toyama Japan

the advancement of digitalization in the manufacturing industry has visualization that enables managers to comprehend the status and operation time of machines, thereby allowing them to identify and address bottlenecks in production lines. Although Gantt charts are commonly used for visualization in the manufacturing industry, there is an increasing need to adopt methods that more effectively visualize past events to facilitate understanding. Consequently, we have developed a Virtual reality (VR) system aimed at improving the operations of small and medium-sized manufacturing enterprises through visualization. By utilizing sensors installed within the factory, we demonstrated that the VR space facilitates comprehensible work analysis instruction and simulation of optimal work processes.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Collaborative Filtering Is a Lie or Not? It Depends on the Shape of Your Data Domain 13

Collaborative Filtering Is a Lie or Not? It Depends on the S...

引用

13th international conference on Electronics, Communications and Networks, CECNet 2023

作者： Wang, Hao CEO Office Ratidar Technologies LLC China

ISBN: (纸本)9781643684802

Recommender systems are versatile. Algorithms such as collaborative filtering, DeepFM and Deep Matrix Factorization can be deployed in different commercial environments without a lot of fundamental modifications. Although there has been hot debate among academic scientists and industrial product owners, environment-sensitive algorithms remain a practice only in real world applications. In this paper, we discuss the topic whether collaborative filtering algorithm is a justified valid model by topological analysis of the problem structures. We claim that the validity of the algorithm is related to the shape of the input data domain. © 2024 the authors and IOS Press.

关键词： Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Accelerating Permute and N-Gram Operations for Hyperdimensional Learning in embedded systems

Accelerating Permute and N-Gram Operations for Hyperdimensio...

引用

ieee international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Pere Vergés Igor Nunes Mike Heddes Tony Givargis Alexandru Nicolau Department of Computer Science University of California Irvine

Hyperdimensional computing (HDC) is a novel computing framework that has gained significant attention for its ability to accelerate machine learning algorithms. Its fast learning and inference capabilities make it an ideal technique for various fields, including machine learning. HDC utilizes high-dimensional holographic vectors, which are vectors with independent and identically distributed dimensions, to represent information. this unique representation allows HDC to leverage highly parallelizable arithmetic operations such as bundling, binding and permute. these simple and highly optimizable operations make HDC an efficient framework for classification in embedded systems. HDC has demonstrated remarkable accuracy in learning patterns from sequenced data. In this paper, we propose a method to enhance the permute operation, which is crucial for maintaining the order of symbols or measures in real-time data. Our method enhances the efficiency of HDC's permute operations by a factor of 10×. Furthermore, by applying the same idea to n-gram encoding, we achieve a speedup of 14×, resulting in up to 26.8× speedup on a real application, compared to a state-of-the-art HDC prototyping library. To achieve this improvement, we utilized SIMD operations and shifted entire SIMD data blocks rather than individual elements. As a result, we demonstrate that real-time inference can be conducted rapidly in applications that are utilized in embedded systems with constrained computational and memory resources, such as those for recognizing emotions, gestures, and language.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Preferred Benchmarking Criteria for Systematic Taxonomy of embedded Platforms (STEP) in Human System Interaction systems 15

Preferred Benchmarking Criteria for Systematic Taxonomy of E...

引用

15th ieee international conference on Human System Interaction (HSI)

作者： Kwasniewska, Alicja Raghava, Sharath Davila, Carlos Sevenier, Mikael Gamba, David Ruminski, Jacek SiMa Technol San Jose CA 95110 USA Gdansk Univ Technol Gdansk Poland

ISBN: (数字)9781665468220

ISBN: (纸本)9781665468220

the rate of progress in the field of Artificial Intelligence (AI) and Machine Learning (ML) has significantly increased over the past ten years and continues to accelerate. Since then, AI has made the leap from research case studies to real production ready applications. the significance of this growth cannot be undermined as it catalyzed the very nature of computing. Conventional platforms struggle to achieve greater performance and efficiency, what causes a surging demand for innovative AI accelerators, specialized platforms and purpose-built computes. At the same time, it is required to provide solutions for assessment of ML platform performance in a reproducible and unbiased manner to be able to provide a fair comparison of different products. this is especially valid for Human System Interaction (HSI) systems that require specific data handling for low latency responses in emergency situations or to improve user experience, as well as for preserving data privacy and security by processing it locally. Taking it into account, this work presents a comprehensive guideline on preferred benchmarking criteria for evaluation of ML platforms that include both lower level analysis of ML models and system-level evaluation of the entire pipeline. In addition, we propose a Systematic Taxonomy of embedded Platforms (STEP) that can be used by the community and customers for better selection of specific ML hardware consistent with their needs for better design of ML-based HSI solutions.

关键词： embedded systems benchmarking system design neural networks machine learning

来源：评论

学校读者我要写书评

暂无评论

Improving the Reaction Latency Analysis of Message Synchronization in ROS

Improving the Reaction Latency Analysis of Message Synchroni...

引用

ieee international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Chenhao Wu Ruoxiang Li Naijun Zhan Nan Guan SKLCS Institution of Software Chinese Academy of Sciences Beijing China City University of Hong Kong Hong Kong SAR School of Computer Science Peking University Beijing China

ISBN: (数字)9798350387957

ISBN: (纸本)9798350387964

Multi-sensor data fusion plays a crucial role in modern autonomous systems, enabling them to perceive the surroundings from multiple dimensions. However, the accuracy of fusion output can be compromised by the temporal inconsistency of input messages from different sources. ROS provides algorithms of message synchronization to mitigate this misalignment before the data fusion process. Nevertheless, this introduces additional latency in processing each message, which influences the real-time performance of ROS systems. Previous research [1] is the first to analyze and bound the reaction latency of the Approximatetime synchronization policy in ROS, which is essential for analyzing the system-level end-to-end reaction time. However, their bound is overly pessimistic. In this paper, we propose a safe and tight reaction latency upper bound for the Approximatetime policy. We conduct experiments to validate its accuracy and assess its improvements compared to [1].

关键词： Accuracy Upper bound Autonomous systems Data integration Approximation algorithms real-time systems Synchronization

来源：评论

学校读者我要写书评

暂无评论

AccTEF: A Transparency and Accountability Evaluation Framework for Ontology-Based systems

引用

international JOURNAL OF SEMANTIC computing 2022年第1期16卷 5-27页

作者： Basereh, Maryam Caputo, Annalina Brennan, Rob Dublin City Univ Sch Comp Glasnevin Campus Dublin Ireland Dublin City Univ Sch Comp ADAPT Ctr Glasnevin Campus Dublin Ireland Dublin City Univ Dublin Sch Comp ADAPT Ctr Dublin 9 Ireland

this paper proposes a new accountability and transparency evaluation framework (AccTEF) for ontology-based systems (OSysts). AccTEF is based on an analysis of the relation between a set of widely accepted data governance principles, i.e. findable, accessible, interoperable, reusable (FAIR) and accountability and transparency concepts. the evaluation of accountability and transparency of input ontologies and vocabularies of OSysts are addressed by analyzing the relation between vocabulary and ontology quality evaluation metrics, FAIR and accountability and transparency concepts. An ontology-based knowledge extraction pipeline is used as a use case in this study. Discovering the relation between FAIR and accountability and transparency helps in identifying and mitigating risks associated with deploying OSysts. this also allows providing design guidelines that help accountability and transparency to be embedded in OSysts. We found that FAIR can be used as a transparency indicator. We also found that the studied vocabulary and ontology quality evaluation metrics do not cover FAIR, accountability and transparency. Accordingly, we suggest these concepts should be considered as vocabulary and ontology quality evaluation aspects. To the best of our knowledge, it is the first time that the relation between FAIR and accountability and transparency concepts has been found and used for evaluation.

关键词： FAIR data semantics AI governance

来源：评论

学校读者我要写书评

暂无评论

time-Sensitive Networking's Scheduled Traffic Implementation on ieee 802.11 COTS Devices

Time-Sensitive Networking's Scheduled Traffic Implementation...

引用

ieee international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Pablo Gutiérrez Peón Paraskevas Karachatzis Wilfried Steiner Elisabeth Uhlemann TTTech Computertechnik AG Vienna Austria School of Innovation Design and Engineering Mälardalen University Västerås Sweden

Wired real-time network deployments based on time-sensitive networking (TSN) are becoming increasingly popular in several application fields including industrial automation and the automotive area. this is to a great extent due to the scheduled traffic (ST; ieee 802.1Qbv), a TSN mechanism that precisely triggers transmissions at pre-defined instants from a set of independent hardware queues. Unfortunately, the wireless counterparts based on ieee 802.11 (Wi-Fi) currently lack standardized or functional solutions that would be able to fulfill strict real-time requirements. this work proposes the use of ST over ieee 802.11, taking advantage of an existing but overlooked mechanism from commercial off-the-shelf (COTS) equipment. An extensive set of tests, spanning different implementation configurations, traffic patterns, and levels of interference evaluates the proposal in terms of reliability and delivery delays and serves as a proof of concept. the tests also evaluate the much-needed clock synchronization quality of an out-of-the-box software-only implementation of the precision time protocol (PTP) due to its relevance in enabling ST.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Task-level thermal Modeling for Temperature Management of Edge TPU

Task-level Thermal Modeling for Temperature Management of Ed...

引用

ieee international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Changhun Han Sangeun Oh Ajou University

ISBN: (数字)9798350387957

ISBN: (纸本)9798350387964

Edge TPU (Tensor Processing Unit) is being widely utilized in various edge computing applications as a high-efficiency, low-power accelerator for deep learning computations. However, temperature rise in Edge TPU can lead to performance degradation, reduced stability, and shortened lifespan, necessitating temperature management through thermal modeling. this paper proposes a task-level thermal modeling technique for predicting Edge TPU temperature. the proposed method estimates power consumption of CPU and Edge TPU based on workloads of various deep learning tasks and predicts the convergence temperature of Edge TPU using a steady temperature model. through experiments, we confirmed that the proposed method accurately predicts Edge TPU temperature for various workloads. the average prediction error was 0.7°C. this study is expected to serve as a foundation for developing temperature management techniques by presenting an effective temperature prediction model that considers the thermal characteristics of Edge TPU.

关键词： Deep learning Temperature Tensors Computational modeling Predictive models thermal management Stability analysis real-time systems thermal stability thermal degradation

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：