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检索条件"任意字段=11th International Conference on Embedded and Real-Time Computing Systems and Applications"

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A Fast Recommendation Algorithm for Data Streams Based on Differential Privacy 11

A Fast Recommendation Algorithm for Data Streams Based on Di...

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11th international conference on Advanced Cloud and Big Data, CBD 2023

作者： Guo, Chang Wang, Xiujun Zheng, Xiao Shao, Xun Mo, Lei Yang, Gaoming AnHui University of Technology School of Computer Science and Technology Ma'Anshan243032 China Toyohashi University of Technology Department of Electrical and Electronic Information Engineering Aichi4418580 Japan Anhui University of Science and Technology School of Computer Science and Engineering Huainan232001 China

ISBN: (纸本)9798350345346

Recommendation systems are an essential tools for people to access interesting information from vast amounts of data and have a wide range of applications. However, current recommendation algorithms encounter persistent challenges, including significant time overhead and limitations in safeguarding user privacy effectively. these challenges stem from their reliance on static clustering algorithms to compress data streams. To tackle these issues, we introduce the Fast Recommendation Algorithm based on Differential Privacy (FRDP) for data streams. FRDP leverages the growing learning vector quantization technique for clustering and compressing data streams in a single pass. Additionally, FRDP dynamically introduces noise based on clustering error to protect individuals' privacy while using differentially private clustering data for recommendation analysis. Finally, we compare the FRDP algorithm with the best existing recommendation algorithms based on two real datasets. Extensive experimental results demonstrate that, while maintaining similar recommendation accuracy under the same privacy protection constraints, the FRDP algorithm achieves substantial time savings, with an average reduction in running time ranging from 55.82% to 59.89%. © 2023 IEEE.

关键词： Recommender systems

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A CNN-based Audio Sensor for Rainfall Estimation: Implementation on embedded Board 11

A CNN-based Audio Sensor for Rainfall Estimation: Implementa...

引用

11th IEEE international conference on Intelligent Data Acquisition and Advanced computing systems - Technology and applications (IDAACS)

作者： Russo, Michele Puglisi, Valerio Francesco Avanzato, Roberta Beritelli, Francesco VICOSYSTEMS SRL Viale Odorico da Pordenone I-95128 Catania Italy Univ Catania DMI Viale Andrea Doria 6 I-95125 Catania Italy Univ Catania DIEEI Viale Andrea Doria 6 I-95125 Catania Italy

ISBN: (纸本)9781665426053

At present, one of the main issues of interest is climate change. It triggers calamitous phenomena (fires, hydrogeological instability and many others) that put crops, vegetation and even human beings at risk. Considering the phenomenon of hydrogeological instability, there is a wide range of smart application contexts (for example, smart city, smart road and smart agriculture), which require a real-time rainfall level monitoring, recognition and classification system. this system is supposed to provide accurate and real-time estimates of rain intensity and alert those in charge in order to reduce the risks associated with the various application contexts. thus, the present paper proposes an audio sensor enabled real-time audio rainfall classification, based on 1-D convolutional neural network (CNN) which offers 95% classification accuracy in five rainfall intensity classes.

关键词： Audio classification Enviroment sound classification Feature extraction techniques Convolutional Neural Networks Multimodal Analysis Rainfall Estimation

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Work-in-Progress Abstract: Revealing and Analyzing Architectural Models in Open-source ArduPilot 27

Work-in-Progress Abstract: Revealing and Analyzing Architect...

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27th IEEE international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Staroletov, Sergey Polzunov Altai State Tech Univ Inst Automat & Electrometry Siberia Russia

ISBN: (纸本)9781665441889

Building robust software can be considered a major challenge in current software engineering processes. this task is especially relevant for the code of cyber-physical systems (CPS) that interact with tangible data of the environment and make decisions that have an impact on the real world. the study of good practices of the architectural organization of such software systems is suitable to conduct on solutions with open-source code, which are developed by large communities of enthusiasts. Such a code bears a long history and has been tested many times on real devices in a real-world environment. the construction of various models using the program code allows us to understand stable architectural solutions, to present them in a graphical form;these solutions can be used in STEM centers when designing other systems, taking into account all the achievements of the communities. In addition, it is possible to propose methods for analyzing models to prove various properties of cyber-physical systems. In this paper, we analyze ArduPilot Mega (APM), an Arduino-compatible solution for building DIY driving and flying systems. the solution is based on a specially designed board with a controller and necessary peripherals, as well as a firmware code in a C++-compatible dialect. Since there are many limitations associated with hardware, it is advisable to carry out a so-called co-modeling, taking into account both hardware and software sides. We consider modeling the interaction of equipment on connected pins and data transmission buses, the software part in the form of a class diagram for the solution. We then describe methods for analyzing the interactions between tasks running on the system through shared variables and evaluating the performance of the task scheduler.

关键词： Analytical models Codes Computational modeling Buildings Cyber-physical systems Software systems Hardware

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Ethernet-Based IDS for Zonal Architecture 11

Ethernet-Based IDS for Zonal Architecture

引用

11th SAEINDIA international Mobility conference, SIIMC 2024

作者： Appajosyula, Kalyansaivitalvamsi Automotive Security Research Group India

In an era where automotive technology is rapidly advancing towards autonomy and connectivity, the significance of Ethernet in ensuring automotive cybersecurity cannot be overstated. As vehicles increasingly rely on high-speed communication networks like Ethernet, the seamless exchange of information between various vehicle components becomes paramount. this paper introduces a pioneering approach to fortifying automotive security through the development of an Ethernet-Based Intrusion Detection System (IDS) tailored for zonal architecture. Ethernet serves as the backbone for critical automotive applications such as advanced driver-assistance systems (ADAS), infotainment systems, and vehicle-to-everything (V2X) communication, necessitating high-bandwidth communication channels to support real-time data transmission. Additionally, the transition from traditional domain-based architectures to zonal architectures underscores Ethernet's role in facilitating efficient communication between different vehicle zones, thereby reducing wiring complexity and enhancing scalability. However, the increasing adoption of Ethernet in automotive networks also brings forth new cybersecurity challenges. Ethernet-based communication introduces vulnerabilities that malicious actors can exploit to compromise vehicle systems' integrity and security. To address these challenges, robust cybersecurity measures are imperative. this paper will introduce various sensors and methods designed to detect intrusions in Ethernet-based automotive architectures. Leveraging insights from the Automotive Open System Architecture (AUTOSAR) specification, innovative IDS models will be developed to monitor and counter threats targeting AUTOSAR diagnostics. these IDS models will utilize advanced detection mechanisms, including signature-based, anomaly-based, and machine-learning techniques, to swiftly identify and neutralize cyber threats in real-time. By seamlessly integrating with AUTOSAR stacks and Ethernet co

关键词： Advanced driver assistance systems

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RT-MongoDB: A NoSQL Database with Differentiated Performance 11

RT-MongoDB: A NoSQL Database with Differentiated Performance

引用

11th international conference on Cloud computing and Services Science (CLOSER)

作者： Andreoli, Remo Cucinotta, Tommaso Pedreschi, Dino Scuola Super Sant Anna Pisa Italy Univ Pisa Pisa Italy

ISBN: (纸本)9789897585104

the advent of Cloud computing and Big Data brought several changes and innovations in the landscape of database management systems. Nowadays, a cloud-friendly storage system is required to reliably support data that is in continuous motion and of previously unthinkable magnitude, while guaranteeing high availability and optimal performance to thousands of clients. In particular, NoSQL database services are taking momentum as a key technology thanks to their relaxed requirements with respect to their relational counterparts, that are not designed to scale massively on distributed systems. Most research papers on performance of cloud storage systems propose solutions that aim to achieve the highest possible throughput, while neglecting the problem of controlling the response latency for specific users or queries. the latter research topic is particularly important for distributed real-time applications, where task completion is bounded by precise timing constraints. In this paper, the popular MongoDB NoSQL database software is modified introducing a per-client/request prioritization mechanism within the request processing engine, allowing for a better control of the temporal interference among competing requests with different priorities. Extensive experimentation with synthetic stress workloads demonstrates that the proposed solution is able to assure differentiated per-client/request performance in a shared MongoDB instance. Namely, requests with higher priorities achieve reduced and significantly more stable response times, with respect to lower priorities ones. this constitutes a basic but fundamental brick in providing assured performance to distributed real-time applications making use of NoSQL database services.

关键词： Cloud computing NoSQL Databases real-time systems

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When FPGAs Meet ADMM with High-level Synthesis (HLS): A real-time Implementation of Long-horizon MPC for Power Electronic systems

When FPGAs Meet ADMM with High-level Synthesis (HLS): A Real...

引用

international conference on Power Electronics (ICPE)

作者： Min Jeong Manuel Schoen Jürgen Biela High Power Electronic Systems (HPE) ETH Zürich

this paper presents a rapid and scalable implementation of an embedded model predictive control (MPC) on a field-programmable gate arrays (FPGA) using a high-level synthesis (HLS) tool. this solution enables a real-time implementation of indirect MPC with a long-prediction horizon, even for systems operating at high switching frequencies. the effectiveness of the proposed method is validated by comparing the required solving time to other solvers and for different embedded platforms for an exemplary three-phase inverter with LCL-filter. the results show that a good operation of the power electronic system up to a switching frequency f sw of 100 kHz can be achieved even on a low-cost FPGA, opening up possibilities to facilitate MPC for a wide range of new applications.

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Adaptive Runtime Estimate of Task Execution times using Bayesian Modeling 27

Adaptive Runtime Estimate of Task Execution Times using Baye...

引用

27th IEEE international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Friebe, Anna Markovic, Filip Papadopoulos, Alessandro, V Nolte, thomas Malardalen Univ Vasteras Sweden

ISBN: (纸本)9781665441889

In the recent works that analyzed execution-time variation of real-time tasks, it was shown that such variation may conform to regular behavior. this regularity may arise from multiple sources, e.g., due to periodic changes in hardware or program state, program structure, inter-task dependence or inter-task interference. Such complexity can be better captured by a Markov Model, compared to the common approach of assuming independent and identically distributed random variables. However, despite the regularity that may be described with a Markov model, over time, the execution times may change, due to irregular changes in input, hardware state, or program state. In this paper, we propose a Bayesian approach to adapt the emission distributions of the Markov Model at runtime, in order to account for such irregular variation. A preprocessing step determines the number of states and the transition matrix of the Markov Model from a portion of the execution time sequence. In the preprocessing step, segments of the execution time trace with similar properties are identified and combined into clusters. At runtime, the proposed method switches between these clusters based on a Generalized Likelihood Ratio (GLR). Using a Bayesian approach, clusters are updated and emission distributions estimated. New clusters can be identified and clusters can be merged at runtime. the time complexity of the online step is O(N<^>2 + NC) where N is the number of states in the Hidden Markov Model (HMM) that is fixed after the preprocessing step, and C is the number of clusters.

关键词： real-time systems Hidden Markov Model Bayesian Analysis Probabilistic Timing Analysis

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A Containerized Microservice Architecture for a ROS 2 Autonomous Driving Software: An End-to-End Latency Evaluation

A Containerized Microservice Architecture for a ROS 2 Autono...

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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

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One-Shot Sparse Neural Architecture Search for Resource-Constrained Devices

One-Shot Sparse Neural Architecture Search for Resource-Cons...

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

作者： Shenghui Song Jan-Nico Zaech Seonyeong Heo School of Computing Kyung Hee University Yongin South Korea INSAIT Sofia University Sofia Bulgaria

ISBN: (数字)9798350387957

ISBN: (纸本)9798350387964

Employing high-performance neural network models is challenging for resource-constrained devices as the models require strong computing power and large memory space. One-shot neural architecture search (NAS) helps to find a suitable neural architecture more efficiently by using a single one-shot network that shares weights with sub-networks. However, the existing one-shot NAS methods pay little attention to the sparsity achievable from the one-shot network. therefore, there still may be room to reduce the resource requirement of the network. this work presents a new one-shot sparse NAS method, which tries to find an optimal sparsity for the network using soft channel masking during the architecture search. the experimental results show that the proposed method can find a more sparse architecture with little accuracy drop.

关键词： Accuracy Computational modeling Neural networks Memory management Machine learning real-time systems

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A Formally Verified Leader Election Algorithm for Autonomous Driving systems

A Formally Verified Leader Election Algorithm for Autonomous...

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

作者： Ryuta Kambe Benjamin Gilby Yuuki Takano TIER IV Inc. Tokyo Japan

ISBN: (数字)9798350387957

ISBN: (纸本)9798350387964

As autonomous driving systems mature, the importance of fault tolerance to provide safe operation even in hazardous conditions becomes a key issue in deployment. In an autonomous driving system composed of redundant devices, it is necessary to maintain consistency across the system regarding which devices should currently be handling processing. In this paper, we present a new leader election algorithm for autonomous driving systems that guarantees consistency in the presence of the failure of any single system component. To make the algorithm practical for autonomous driving systems, we design it to both handle network link failures and guarantee liveness in the presence of a single failure. Due to the safety-critical nature of our environment and the known difficulty of testing distributed algorithms, we use formal verification to validate our proposed algorithm. Our experiments show that the algorithm completes with reasonable time in a simulated environment of an autonomous driving system.

关键词： Fault tolerance Voting Fault tolerant systems real-time systems Distributed algorithms Autonomous vehicles Formal verification Testing

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