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

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

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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.

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A Reverse Design Framework for Modifiable-off-the-Shelf embedded systems: Application to Open-Source Autopilots 11th

A Reverse Design Framework for Modifiable-off-the-Shelf Emb...

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11th international conference on Model and Data Engineering, MEDI 2022

作者： Kamni, Soulimane Ouhammou, Yassine Grolleau, Emmanuel Bertout, Antoine Hattenberger, Gautier LIAS ISAE-ENSMA Futuroscope France Université de Poitiers Futuroscope France Ecole Nationale de l’Aviation Civile Université de Toulouse Toulouse France

ISBN: (纸本)9783031215940

the development of real-time embedded systems is usually preceded by an important design phase to ensure that functional and behavioural constraints are met. However, the modification of some systems, especially Unmanned Air Vehicles that need to be frequently customised, is typically done in an ad-hoc way. Indeed, the design information may not be available, which may affect the proper functioning of the system. this paper aims to propose a framework helping reverse-engineering a Modifiable Off-the-Shelf (MOTS) embedded system in order to be able to ease its modification. In other words, our objective is to point out where modifications have to happen, and allow smooth use of third-party analysis and/or architecture exploration tools to re-analyse non-functional properties (safety, performances, etc.) regarding the customisation. this framework extracts functional-chains from the source code and represents them visually as a model-based design by using model-driven engineering settings. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Reverse engineering

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Efficient Multipath Selection for IoT Video Transmission 11

Efficient Multipath Selection for IoT Video Transmission

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11th IEEE international conference on Cloud Networking (CloudNet)

作者： Bhering, Fabiano Passos, Diego Albuquerque, Celio Obraczka, Katia Univ Fed Fluminense UFF Ctr Fed Educ Tecnol CEFET MG Niteroi Brazil Univ Fed Fluminense UFF Niteroi Brazil ISEL Inst Super Engn Lisbon Portugal Univ Calif Santa Cruz UCSC Santa Cruz CA USA

ISBN: (数字)9781665486279

ISBN: (纸本)9781665486279

In IoT video applications, such as public transportation and traffic monitoring, video is often transmitted over a multi-hop wireless network and has stringent Quality of Service requirements. While multipath routing has been proposed as an effective strategy for supporting this demand, it should select paths that meet the requirements of the driving video application in a timely manner. In this paper, we introduce FITPAth, an efficient and adaptable path selection scheme for multipath routing that can accommodate scenarios where multiple video sources can simultaneously transmit heterogeneous video flows, i.e., flows of different bitrates. FITPAth uses a novel heuristic-based iterative optimization approach that estimates the conditions of the underlying network in real time while accounting for the different bitrate requirements of the application video flows. We show FITPAth outperforms various existing path selection mechanisms both in terms of user QoE and network performance. We also evaluate FITPAth's convergence to demonstrate that it can be used in practice to quickly generate solutions with adequate video quality while incrementally improving QoE as the algorithm iterates.

关键词： Heuristic algorithms Wireless networks Bit rate Streaming media Routing real-time systems Quality of experience

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

Visualization System Using Virtual Reality for Work Improvem...

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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.

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An Amalgamation of Machine Learning and embedded systems for Smart Street Lightning systems

An Amalgamation of Machine Learning and Embedded Systems for...

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international conference on computing for Sustainable Global Development (INDIACom)

作者： Sakshi Gupta Rishit Singh Jolly Parikh Yugnanda Puri Ridham Vashisht Department of Electronics and Communication Engineering Bharati Vidyapeeth’s College of Engineering New Delhi Department of Computer Science and Engineering Bharati Vidyapeeth’s College of Engineering New Delhi

this research paper introduces an innovative Smart Street Light System that optimizes street lighting operations by harnessing ambient light levels to govern the activation and deactivation of streetlights. Lux value thresholds are employed to distinguish between various lighting scenarios, ranging from bright sunlight to subdued sunlight and complete darkness. Moreover, the paper explores the potential integration of an ultrasonic sensor (US 100) for detecting approaching vehicles and pedestrians, by using advanced machine learning algorithms, thereby enhancing system capabilities. the novel use of Machine Learning algorithms, extensive training of the model, on dataset built using real world conditions, enhances the output accuracy of the model, which gives the model the capabilities to take decisions on its own and thus create a self-sustainable ecosystem, harnessing advanced technologies, without any human involvement. the model was created and implemented with an accuracy of 97.35 percent.

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Demand Characterization of CPS with Conditionally-Enabled Sensors 27

Demand Characterization of CPS with Conditionally-Enabled Se...

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

作者： Willcock, Aaron Fisher, Nathan Chantem, thidapat Wayne State Univ Dept Comp Sci Detroit MI 48202 USA Virginia Tech Dept Elect & Comp Engn Arlington VA USA

ISBN: (纸本)9781665441889

Characterizing computational demand of Cyber-Physical systems (CPS) is critical for guaranteeing that multiple hard real-time tasks may be scheduled on shared resources without missing deadlines. In a CPS involving repetition such as industrial automation systems found in chemical process control or robotic manufacturing, sensors and actuators used as part of the industrial process may be conditionally enabled (and disabled) as a sequence of repeated steps is executed. In robotic manufacturing, for example, these steps may be the movement of a robotic arm through some trajectories followed by activation of end-effector sensors and actuators at the end of each completed motion. the conditional enabling of sensors and actuators produces a sequence of Monotonically Ascending Execution times (MAE) with lower WCET when the sensors are disabled and higher WCET when enabled. Since these systems may have several predefined steps to follow before repeating the entire sequence each unique step may result in several consecutive sequences of MAE. the repetition of these unique sequences of MAE result in a repeating WCET sequence. In the absence of an efficient demand characterization technique for repeating WCET sequences composed of subsequences with monotonically increasing execution time, this work proposes a new task model to describe the behavior of real-world systems which generate large repeating WCET sequences with subsequences of monotonically increasing execution times. In comparison to the most applicable current model, the Generalized Multiframe model (GMF), an empirically and theoretically faster method for characterizing the demand is provided. the demand characterization algorithm is evaluated through a case study of a robotic arm and simulation of 10,000 randomly generated tasks where, on average, the proposed approach is 231 and 179 times faster than the state-of-the-art in the case study and simulation respectively.

关键词： real-time systems control systems cyberphysical systems

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Adaptive Admission Control Policy in Distributed real time Database System 11

Adaptive Admission Control Policy in Distributed Real Time D...

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11th international conference on System Modeling and Advancement in Research Trends, SMART 2022

作者： Chauhan, Nupa Ram Dwivedi, Rakesh Kumar CCSIT Tmu Computer Science and Engineering Moradabad India

ISBN: (纸本)9781665487320

Today's real time computers activities and applications required data services in the distributed platform where real time applications have been needed for databases, in which data and operations have special characteristics in terms of time constraints. It stores large amount of data with time-sensitive manner and process it within fix given time frame. the requirement for real time computers activities and its applications are increasing in distributed real time database system (DRTDBS) including advanced traffic control, global environment control, nationwide power grid control etc. the transaction work load in DRTDBS has not balanced and the transaction processing patterns have time varying and distorted. Due to the unbalanced computation workload on DRTDBS and unpredictable communication delay can lead to miss the large number of transaction deadline. Hence, an adaptive admission control architecture and protocol have required for DRTDBS. the Adaptive admission Control Policy has fulfil to accessing and maintaining real time computers activities and application of data for satisfy timing constraints of transaction supported applications. this paper presents an adaptive admission control architecture and an efficient set of protocol. the local controller controls the local transaction request and global load balancer works global transaction request on distributed environment. the functionality of Adaptive Admission Control Policy have increased the performance because minimizing the miss ratio and increasing throughput. the experiment results show that an adaptive admission control policy effectively balances the workload in distributed real time database system under tight transaction workload as compared to existing protocols. © 2022 IEEE.

关键词： Distributed database systems

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Recovery-by-Learning: Restoring Autonomous Cyber-physical systems from Sensor Attacks 27

Recovery-by-Learning: Restoring Autonomous Cyber-physical Sy...

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

作者： Akowuah, Francis Prasad, Romesh Espinoza, Carlos Omar Kong, Fanxin Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA Syracuse Univ Dept Mech & Aerosp Engn Syracuse NY 13244 USA

ISBN: (纸本)9781665441889

Autonomous cyber-physical systems (CPS) are susceptible to non-invasive physical attacks such as sensor spoofing attacks that are beyond the classical cybersecurity domain. these attacks have motivated numerous research efforts on attack detection, but little attention on what to do after detecting an attack. the importance of attack recovery is emphasized by the need to mitigate the attack's impact on a system and restore it to continue functioning. there are only a few works addressing attack recovery, but they all rely on prior knowledge of system dynamics. To overcome this limitation, we propose Recovery-by-Learning, a data-driven attack recovery framework that restores CPS from sensor attacks. the framework leverages natural redundancy among heterogeneous sensors and historical data for attack recovery. Specially, the framework consists of two major components: state predictor and data checkpointer. First, the predictor is triggered to estimate systems states after the detection of an attack. We propose a deep learning-based prediction model that exploits the temporal correlation among heterogeneous sensors. Second, the checkpointer executes when no attack is detected. We propose a double sliding window based checkpointing protocol to remove compromised data and keep trustful data as input to the state predictor. third, we implement and evaluate the effectiveness of our framework using a realistic data set and a ground vehicle simulator. the results show that our method restores a system to continue functioning in presence of sensor attacks.

关键词： autonomous cyber-physical systems sensor attacks attack recovery attack resiliency

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Improving the Reaction Latency Analysis of Message Synchronization in ROS

Improving the Reaction Latency Analysis of Message Synchroni...

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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

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Testing Methods for Blockchain applications 11th

Testing Methods for Blockchain Applications

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11th international conference on High-Performance computing systems and Technologies in Scientific Research, Automation of Control and Production (HPCST)

作者： Staroletov, Sergey Galkin, Roman Polzunov Altai State Tech Univ Barnaul 656038 Russia WinteX Solut LLC Wintexpro Barnaul 656049 Russia

ISBN: (纸本)9783030941413;9783030941406

A blockchain application is a form of modern software that runs in its ecosystem and interacts with other application instances. Such applications run decentralized on a large number of nodes and process requests from a large number of users. thus, they are high-performance applications that are prone to specific errors due to difficult-to-predict network behavior. In addition, they are predisposed to errors inherent in all software systems. Since bugs can potentially lead to losing an immense amount of funds in cryptocurrencies, learning howto test such applications is an important task. In this paper, we explore the internal quality assurance methods of the Bitcoin and Ethereum platforms at their various levels of logical organization. Next, we describe our test bench designed for functional testing of cryptocurrency payment gateways. the solution provides a software abstraction for making API calls to virtualized nodes of various platforms using emulators of real blockchain networks.

关键词： Software testing Ethereum Bitcoin RPC

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