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检索条件"任意字段=IEEE International Conference on Embedded and Real-Time Computing Systems and Applications"

共 36882 条记录，以下是411-420 订阅

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Evolving Neuro-Fuzzy systems for real-time Data Processing in Internet of Medical Things 4

Evolving Neuro-Fuzzy Systems for Real-Time Data Processing i...

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4th international conference on Emerging Trends in Networks and Computer Communications, ETNCC 2024

作者： Chilipa, Richard Nyirenda, Clement University of the Western Cape Department of Computer Science Cape Town South Africa

ISBN: (纸本)9798350353266

Evolving neuro-fuzzy systems (ENFS) have shown great promise in analysis of streaming data, integrating artificial neural networks and fuzzy logic to create self-learning, data-driven models suitable for online (real-time) applications. In healthcare, ENFS have the potential to transform the Internet of Medical Things (IoMT) by enabling real-time data processing, decision support, and timely emergency response. In this study six evolving fuzzy min-max neural network models have been implemented using Python and Kafka, and evaluated on the MIT-BIH Arrhythmia dataset comprising 109,446 samples corresponding to shapes of heartbeats for the normal case and the cases affected by different arrhythmias and myocardial infarction. To achieve online continual learning, the prequential test-then-train method has been used to sequentially classify the data instances from scratch and update the system structure along with the arrival of new data samples. The Enhanced Fuzzy Min-Max Neural Network (EFMMNN) achieved the highest accuracy of 98.11 %. Future work will explore deploying these evolving fuzzy systems in real-world healthcare settings using edge-fog computing. © 2024 ieee.

关键词： Fog computing

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Improved Bus Contention Analysis for 3-Phase Tasks 29

Improved Bus Contention Analysis for 3-Phase Tasks

引用

29th ieee international conference on embedded and real-time computing systems and applications, RTCSA 2023

作者： Arora, Jatin Rashid, Syed Aftab Nelissen, Geoffrey Maia, Claudio Tovar, Eduardo CISTER ISEP Porto Portugal VORTEX CoLab Portugal Eindhoven University of Technology Eindhoven Netherlands

ISBN: (纸本)9798350337860

The 3-phase task execution model has shown to be a good candidate to tackle the memory bus contention problem. It divides the execution of tasks into computation and memory phases that enable a fine-grained memory bus contention analysis. However, existing works that focus on the bus contention analysis for 3-phase tasks, neglect the fact that memory bus contention strongly relates to the number of bus/memory requests generated by tasks, which, in turn, depends on the content of the cache memories during the execution of those tasks. These existing works assume that the worst-case number of bus/memory requests will be generated during all the memory phases of all tasks, irrespective of the already existing content in the cache memory. This overestimates the memory bus contention of tasks, leading to pessimistic worst-case response time (WCRT) bounds. This work proposes a holistic approach towards bus contention analysis for 3-phase tasks by (1) deriving an upper bound on the actual cache misses of tasks that lead to bus/memory requests;(2) improving State-of-the-Art (SOTA) bus contention analysis of two bus arbitration schemes that dominate all existing works on the bus contention analysis for 3-phase tasks;and (3) performing an extensive experimental evaluation under different settings to compare the proposed analysis against the SOTA. Results show that incorporating a tighter bound on the number of cache misses of tasks into the bus contention analysis can lead to a significant improvement in the task set schedulability. © 2023 ieee.

关键词： real time systems

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An Enhanced Image Loading Framework for Social Media applications 3

An Enhanced Image Loading Framework for Social Media Applica...

引用

3rd international conference on Advances in computing, Communication, embedded and Secure systems, ACCESS 2023

作者： Rani S, Siji Nair, Lekshmi S Vaisakh, M.S. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Amritapuri India

ISBN: (纸本)9798350346169

Online Social network (OSN) is the most popular platform where users prefer to share images and videos. Image loading time in social media applications is time-consuming due to significantly less internet bandwidth. Uploading an image on a social media platform demands accurate size, highest quality, format, and resolution. Often, duplicates of images may be uploaded by the user accidentally. Uploading images or videos by individual users on platforms like Facebook or Instagram is Content loading. In this article, we suggest a suitable method for reducing the content loading time by finding the duplicate images and replacing those images with the original image that is already loaded using ANNOY (Artificial Neural Network Oh Yeah). In the methodology we could successfully reduce the image loading time by checking the duplication. © 2023 ieee.

关键词： Social networking (online)

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The SPATIAL Architecture: Design and Development Experiences from Gauging and Monitoring the AI Inference Capabilities of Modern applications 44

The SPATIAL Architecture: Design and Development Experiences...

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44th ieee international conference on Distributed computing systems (ICDCS)

作者： Ottun, Abdul-Rasheed Marasinghe, Rasinthe Elemosho, Toluwani Liyanage, Mohan Ragab, Mohamad Bagave, Prachi Westberg, Marcus Asadi, Mehrdad Boerger, Michell Sandeepa, Chamara Senevirathna, Thulitha Siniarski, Bartlomiej Liyanage, Madhusanka La, Vinh Hoa Nguyen, Manh-Dung de Oca, Edgardo Montes Oomen, Tessa Goncalves, Joao Fernando Ferreira Tanaskovic, Illija Klopanovic, Sasa Kourtellis, Nicolas Soriente, Claudio Pridmore, Jason Cavalli, Ana Rosa Draskovic, Drasko Marchal, Samuel Wang, Shen Nogueroll, David Solans Tcholtchev, Nikolay Ding, Aaron Yi Flores, Huber Univ Tartu Tartu Estonia Delft Univ Technol Delft Netherlands Fraunhofer Inst Open Commun Syst Berlin Germany Univ Coll Dublin Dublin Ireland Montimage Paris France VTT Tech Res Ctr Finland Ltd Espoo Finland Mainflux Belgrade Serbia Erasmus Univ Rotterdam Netherlands NEC Labs Heidelberg Germany Univ Southampton Southampton Hants England Telefonica Res Madrid Spain Vrije Univ Brussel Brussels Belgium RheinMain Univ Appl Sci Wiesbaden Germany

ISBN: (纸本)9798350386066;9798350386059

Despite its enormous economical and societal impact, lack of human-perceived control and safety is re-defining the design and development of emerging AI-based technologies. New regulatory requirements mandate increased human control and oversight of AI, transforming the development practices and responsibilities of individuals interacting with AI. In this paper, we present the SPATIAL architecture, a system that augments modern applications with capabilities to gauge and monitor trustworthy properties of AI inference capabilities. To design SPATIAL, we first explore the evolution of modern system architectures and how AI components and pipelines are integrated. With this information, we then develop a proof-of-concept architecture that analyzes AI models in a human-in-the-loop manner. SPATIAL provides an AI dashboard for allowing individuals interacting with applications to obtain quantifiable insights about the AI decision process. This information is then used by human operators to comprehend possible issues that influence the performance of AI models and adjust or counter them. Through rigorous benchmarks and experiments in real-world industrial applications, we demonstrate that SPATIAL can easily augment modern applications with metrics to gauge and monitor trustworthiness, however, this in turn increases the complexity of developing and maintaining systems implementing AI. Our work highlights lessons learned and experiences from augmenting modern applications with mechanisms that support regulatory compliance of AI. In addition, we also present a road map of on-going challenges that require attention to achieve robust trustworthy analysis of AI and greater engagement of human oversight.

关键词： Trustworthy AI AI Act Industrial Use Cases Accountability Resilience Human Oversight Practical Trustworthiness

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Anomaly Detection and Functional Testing for Automotive CAN Communication 18

Anomaly Detection and Functional Testing for Automotive CAN ...

引用

18th Annual ieee international systems conference (SysCon)

作者： Al Maruf, Md Azim, Akramul Ontario Tech Univ Dept Elect Comp & Software Engn Oshawa ON Canada

ISBN: (纸本)9798350358810;9798350358803

Integrated vehicle dynamics control systems require real-time communication among their components to improve performance and process efficiency. This communication relies on the use of sensor data, hardware interfaces, transmission protocols, and control strategies, which all have an impact on the system's reliability. However, as the number of functionalized electronic control units (ECUs) and wiring systems increases, advanced control systems encounter complex functional and cybersecurity issues. To mitigate this complexity, the automotive industry widely employs the Controller Area Network (CAN) communication bus. Nevertheless, the inherent vulnerabilities of CAN and the rich interfaces with external environments increase the systems' susceptibility to soft errors caused by uncertainty factors such as process changes. Therefore, detecting abnormalities in automotive CAN communication is crucial. This paper introduces a machine learning (ML)-based anomaly detection framework to identify anomalies through CAN messages, extracting key features and employing ML models for predictive analysis. It also uses Triple Modular Redundancy (TMR) for trusted ML computation in anomaly detection. The study provides a comparative analysis of various ML algorithms, highlighting the effectiveness of Deep Neural Networks in identifying anomalies within both synthetic and real Hyundai CAN data for a wheel speed control system, showcasing the framework's capability to enhance system reliability and security.

关键词： CAN Communication Anomaly Detection embedded systems

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Performance Analysis of ZNS-aware File systems on Distributed applications 43

Performance Analysis of ZNS-aware File Systems on Distribute...

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43rd ieee international conference on Distributed computing systems (ICDCS)

作者： Cho, Yongwoo Park, Seongsoo Han, Hwansoo Sungkyunkwan Univ Comp Sci & Engn Suwon South Korea Sungkyunkwan Univ HPC Res Ctr Suwon South Korea

ISBN: (纸本)9798350339864

Recently, ZNS SSDs have been actively researched to handle the functions of the FTL directly on the host system. ZNS SSDs can improve the I/O performance and spatial efficiency of SSDs by eliminating GC and eliminating overprovisioning. In this paper, we analyze the performance by running distributed applications on a file system which supports ZNS SSDs. We found that much of the time difference occurs in the process of executing open and unlink operations rather than the performance of read and write operations. It has been confirmed that the performance difference of read/write operations is not significant for the applications. If structural optimization is made on file system, it has been found that ZNS SSDs are better than CNS SSDs of the same capacity in terms of price.

关键词： solid state drive zoned namespace file system

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Technical Report: Consistency Assurance for Edge-Assisted Multi-Party computing and Transport-Intensive applications 3

Technical Report: Consistency Assurance for Edge-Assisted Mu...

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3rd ieee international conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2024

作者： Mei, Wenming Zhang, Lizhi Song, Wen Sun, Yunqi China State Grid Corporation of China Beijing China State Grid Electric Power Research Institute Nanjing China Nanjing University Nanjing China

ISBN: (纸本)9798350380989

In the rapidly evolving digital era, we have witnessed the rise of computation-intensive and transmission-intensive applications like multi-party real-time video communication, remote medical surgeries, and online education. Cloud-edge collaborative resource scheduling has been pivotal in enhancing computational efficiency and reducing end-to-end latency for such applications. However, providing services while ensuring system consistency presents a new challenge in multiparty settings. This study focuses on efficient resource scheduling within cloud-edge collaborative environments, especially addressing system consistency. We propose an innovative real-time consistency assurance model based on latency differentiation aimed at optimizing real-time consistency issues in cloud-edge settings while ensuring data accuracy and timeliness. This problem falls within integer programming, which can transform into a convex optimization issue, efficiently solvable via convex optimization methods. The solution effectively addresses consistency in resource scheduling, significantly improving overall system performance and reliability. Experimental results demonstrate that our method is suitable for computation-intensive and transmission-intensive tasks, substantially enhancing the system's consistency performance and providing robust technical support for the design and optimization of practical cloud-edge collaborative systems. © 2024 ieee.

关键词： Cloud-edge collaborative resource scheduling Integer programming real-time consistency

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real-time Monitoring and Trace Based on Nested COBS 3

Real-Time Monitoring and Trace Based on Nested COBS

引用

3rd ieee Industrial Electronics Society Annual On-Line conference, ONCON 2024

作者： Lindgren, Per Dzialo, Pawel Luleå University of Technology Sweden Tampere University Finland

ISBN: (纸本)9798331540319

Monitoring and tracing are integral to embedded systems development. In context of real-time systems, overhead is of essence as the timing behavior might be affected. In this paper we present real-time Monitor and Trace (RTMT) targeting (hard) real-time systems with static priority preemptive scheduling. Features of RTMT include both traditional logging capabilities, as well as event monitoring functionality. We show its feasibility to the Hippomenes FPGA implementation of the RISC-V RT architecture and demonstrate that cycle accurate time stamping of interrupt entry/exit and resource locking/unlocking is possible with zero interference to the running application. Logging, on the other hand comes with constant time overhead and is guaranteed to be non-blocking. RTMT builds on Nested COBS (N-COBS), a novel extension of the COBS protocol allowing for static priority preemptive framing with single byte overhead. In the paper we present the N-COBS protocol, formalize and prove its key properties: protocol soundness, encoder/decoder reversibility and single byte overhead. Design simplicity is demonstrated by the provided System Verilog encoder implementation as used to showcase monitoring and tracing of Rust RTIC applications running on the RISC-V RT architecture. © 2024 ieee.

关键词： embedded systems

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Comparitive Analysis of Deep Learning Techniques for Assistive Soft Wearable Robots 3

Comparitive Analysis of Deep Learning Techniques for Assisti...

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3rd international conference on Advances in computing, Communication, embedded and Secure systems, ACCESS 2023

作者： Chandran, Ranjeesh R Chakrapani, V Yogeshwar Krishnan, Sreedeep Dharmaraj, D Ganeshaperumal Kalasalingam Academy of Research and Education Deptartment of Instrumentation and Control Engineering Tamil Nadu Srivilliputhur India

ISBN: (纸本)9798350346169

A new innovation called wearable assistive robotics has the potential of assisting those with sensorimotor disabilities in doing routine tasks. A lot of research is done on soft robots because of its adaptability, deformability, and flexibility. In contrast to soft robots and rigid robots, face obstacles in control, calibration, and modelling because the properties of soft materials which result in complex behaviors due to hysteresis and non-linearity. The use of deep learning techniques in real-time poses additional challenges for researchers when it comes to accuracy and equipment cost. Recent research has used various deep learning algorithms to address these constraints. This paper gives deep insight and analysis of existing deep learning techniques in the area of assistive soft wearable robotics and classifies their applicability in various soft robotic applications. The current constraints in the study field, along with an analysis of various deep learning models with regard to various types of assistive soft wearable robot applications, are provided, followed by a description and implementation of the available deep learning techniques for assistive soft wearable robotics. © 2023 ieee.

关键词： Robot applications

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real-time Sign Language Detection Using Deep Learning

Real-Time Sign Language Detection Using Deep Learning

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2025 ieee international conference on Computational, Communication and Information Technology, ICCCIT 2025

作者： Selvi, A. Senthil Ratiraju, Gautham Jeevan, Akhil Reddy, Jinnam Sai Kiran Krishna, Molakalapalli Vamsi Senthil Pandi, S. SRM IST Dept of CSE Ramapuram Chennai India Rajalakshmi Engineering College Department of CSE Chennai India

ISBN: (纸本)9798331512965

Sign language is the primary mode of communication for deaf and hard of hearing community. This paper discusses the development of a real time sign language recognition system by deploying deep learning techniques. For instance, the aim is to establish a good model which could be used to identify different hand gestures as used in sign languages. Once trained on a data set of 10 different hand gestures, the system is able to recognize and predict gestures in other images. The use of TensorFlow and Keras in the implementation ensures scalability of the system for real-time application. This method aims at assisting the deaf and mute people by developing an application that will improve their social life. Furthermore, TensorFlow and Python facilitate the porting of the system to mobile and embedded systems, which enhance its reach among different gadgets. This system is intended to help avoid one of the main concerns of sign language users in which they have limited ability to interact with others and thus limited engagement with basic services. The objective of the researcher is to make the quality of life of sign language users better by translating their gestures into a format that is easier to understand. © 2025 ieee.

关键词： embedded systems

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