Subjects -> COMPUTER SCIENCE (Total: 2313 journals)
    - ANIMATION AND SIMULATION (33 journals)
    - ARTIFICIAL INTELLIGENCE (133 journals)
    - AUTOMATION AND ROBOTICS (116 journals)
    - CLOUD COMPUTING AND NETWORKS (75 journals)
    - COMPUTER ARCHITECTURE (11 journals)
    - COMPUTER ENGINEERING (12 journals)
    - COMPUTER GAMES (23 journals)
    - COMPUTER PROGRAMMING (25 journals)
    - COMPUTER SCIENCE (1305 journals)
    - COMPUTER SECURITY (59 journals)
    - DATA BASE MANAGEMENT (21 journals)
    - DATA MINING (50 journals)
    - E-BUSINESS (21 journals)
    - E-LEARNING (30 journals)
    - ELECTRONIC DATA PROCESSING (23 journals)
    - IMAGE AND VIDEO PROCESSING (42 journals)
    - INFORMATION SYSTEMS (109 journals)
    - INTERNET (111 journals)
    - SOCIAL WEB (61 journals)
    - SOFTWARE (43 journals)
    - THEORY OF COMPUTING (10 journals)

AUTOMATION AND ROBOTICS (116 journals)                     

Showing 1 - 101 of 101 Journals sorted alphabetically
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 10)
ACM Transactions on Human-Robot Interaction     Open Access   (Followers: 4)
Advanced Robotics     Hybrid Journal   (Followers: 29)
Advances in Computed Tomography     Open Access   (Followers: 2)
Advances in Image and Video Processing     Open Access   (Followers: 27)
Advances in Robotics & Automation     Open Access   (Followers: 12)
Artificial Life and Robotics     Hybrid Journal   (Followers: 17)
Augmented Human Research     Hybrid Journal  
Automated Software Engineering     Hybrid Journal   (Followers: 9)
Automatic Control and Information Sciences     Open Access   (Followers: 4)
Automation and Remote Control     Hybrid Journal   (Followers: 6)
Autonomous Agents and Multi-Agent Systems     Hybrid Journal   (Followers: 9)
Autonomous Robots     Hybrid Journal   (Followers: 11)
Biocybernetics and Biological Engineering     Full-text available via subscription   (Followers: 4)
Biological Cybernetics     Hybrid Journal   (Followers: 10)
Biomimetic Intelligence and Robotics     Open Access  
Cognitive Robotics     Open Access   (Followers: 4)
Computational Intelligence and Neuroscience     Open Access   (Followers: 18)
Computer-Aided Design     Hybrid Journal   (Followers: 9)
Construction Robotics     Hybrid Journal   (Followers: 5)
Current Robotics Reports     Hybrid Journal   (Followers: 4)
Cybernetics & Human Knowing     Full-text available via subscription   (Followers: 3)
Cybernetics and Systems Analysis     Hybrid Journal  
Cybernetics and Systems: An International Journal     Hybrid Journal   (Followers: 1)
Design Automation for Embedded Systems     Hybrid Journal   (Followers: 4)
Digital Zone : Jurnal Teknologi Informasi Dan Komunikasi     Open Access  
Drone Systems and Applications     Open Access   (Followers: 1)
Electrical Engineering and Automation     Open Access   (Followers: 9)
Facta Universitatis, Series : Automatic Control and Robotics     Open Access   (Followers: 1)
Foundations and Trends® in Robotics     Full-text available via subscription   (Followers: 4)
GIScience & Remote Sensing     Open Access   (Followers: 58)
IAES International Journal of Robotics and Automation     Open Access   (Followers: 5)
IEEE Robotics & Automation Magazine     Full-text available via subscription   (Followers: 69)
IEEE Robotics and Automation Letters     Hybrid Journal   (Followers: 9)
IEEE Transactions on Affective Computing     Hybrid Journal   (Followers: 23)
IEEE Transactions on Audio, Speech, and Language Processing     Hybrid Journal   (Followers: 17)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 70)
IEEE Transactions on Cybernetics     Hybrid Journal   (Followers: 16)
IEEE Transactions on Intelligent Vehicles     Hybrid Journal   (Followers: 2)
IEEE Transactions on Medical Robotics and Bionics     Hybrid Journal   (Followers: 5)
IEEE Transactions on Neural Networks and Learning Systems     Hybrid Journal   (Followers: 57)
IEEE Transactions on Robotics     Hybrid Journal   (Followers: 71)
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews     Hybrid Journal   (Followers: 16)
IET Cyber-systems and Robotics     Open Access   (Followers: 2)
IET Systems Biology     Open Access   (Followers: 1)
Industrial Robot An International Journal     Hybrid Journal   (Followers: 2)
Intelligent Control and Automation     Open Access   (Followers: 6)
Intelligent Service Robotics     Hybrid Journal   (Followers: 2)
International Journal of Adaptive, Resilient and Autonomic Systems     Full-text available via subscription   (Followers: 3)
International Journal of Advanced Pervasive and Ubiquitous Computing     Full-text available via subscription   (Followers: 4)
International Journal of Advanced Robotic Systems     Full-text available via subscription   (Followers: 1)
International Journal of Agent Technologies and Systems     Full-text available via subscription   (Followers: 4)
International Journal of Ambient Computing and Intelligence     Full-text available via subscription   (Followers: 3)
International Journal of Applied Evolutionary Computation     Full-text available via subscription   (Followers: 3)
International Journal of Artificial Life Research     Full-text available via subscription  
International Journal of Automation and Control     Hybrid Journal   (Followers: 11)
International Journal of Automation and Control Engineering     Open Access   (Followers: 5)
International Journal of Automation and Logistics     Hybrid Journal   (Followers: 4)
International Journal of Automation and Smart Technology     Open Access   (Followers: 3)
International Journal of Bioinformatics Research and Applications     Hybrid Journal   (Followers: 14)
International Journal of Biomechatronics and Biomedical Robotics     Hybrid Journal   (Followers: 2)
International Journal of Humanoid Robotics     Hybrid Journal   (Followers: 6)
International Journal of Imaging & Robotics     Full-text available via subscription   (Followers: 3)
International Journal of Intelligent Information Technologies     Full-text available via subscription   (Followers: 1)
International Journal of Intelligent Machines and Robotics     Hybrid Journal   (Followers: 3)
International Journal of Intelligent Mechatronics and Robotics     Full-text available via subscription   (Followers: 5)
International Journal of Intelligent Robotics and Applications     Hybrid Journal  
International Journal of Intelligent Systems Design and Computing     Hybrid Journal   (Followers: 2)
International Journal of Intelligent Unmanned Systems     Hybrid Journal   (Followers: 3)
International Journal of Machine Consciousness     Hybrid Journal   (Followers: 7)
International Journal of Machine Learning and Cybernetics     Hybrid Journal   (Followers: 31)
International Journal of Mechanisms and Robotic Systems     Hybrid Journal   (Followers: 2)
International Journal of Mechatronics and Automation     Hybrid Journal   (Followers: 5)
International Journal of Robotics and Automation     Full-text available via subscription   (Followers: 8)
International Journal of Robotics and Control     Open Access   (Followers: 3)
International Journal of Robotics Applications and Technologies     Full-text available via subscription   (Followers: 1)
International Journal of Robotics Research     Hybrid Journal   (Followers: 15)
International Journal of Space-Based and Situated Computing     Hybrid Journal   (Followers: 2)
International Journal of Synthetic Emotions     Full-text available via subscription  
International Journal of Tomography & Simulation     Full-text available via subscription   (Followers: 1)
Journal of Automation and Control     Open Access   (Followers: 9)
Journal of Computer Assisted Tomography     Hybrid Journal   (Followers: 2)
Journal of Control & Instrumentation     Full-text available via subscription   (Followers: 19)
Journal of Control, Automation and Electrical Systems     Hybrid Journal   (Followers: 11)
Journal of Intelligent and Robotic Systems     Hybrid Journal   (Followers: 6)
Journal of Intelligent Learning Systems and Applications     Open Access   (Followers: 4)
Journal of Robotic Surgery     Hybrid Journal   (Followers: 3)
Jurnal Otomasi Kontrol dan Instrumentasi     Open Access  
Machine Translation     Hybrid Journal   (Followers: 12)
Proceedings of the ACM on Human-Computer Interaction     Hybrid Journal   (Followers: 2)
Results in Control and Optimization     Open Access   (Followers: 5)
Revista Iberoamericana de Automática e Informática Industrial RIAI     Open Access  
ROBOMECH Journal     Open Access   (Followers: 1)
Robotic Surgery : Research and Reviews     Open Access   (Followers: 1)
Robotica     Hybrid Journal   (Followers: 5)
Robotics and Autonomous Systems     Hybrid Journal   (Followers: 19)
Robotics and Biomimetics     Open Access   (Followers: 1)
Robotics and Computer-Integrated Manufacturing     Hybrid Journal   (Followers: 7)
Science Robotics     Full-text available via subscription   (Followers: 11)
Unmanned Systems     Hybrid Journal   (Followers: 4)
Wearable Technologies     Open Access   (Followers: 4)

           

Similar Journals
Journal Cover
Design Automation for Embedded Systems
Journal Prestige (SJR): 0.172
Citation Impact (citeScore): 1
Number of Followers: 4  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1572-8080 - ISSN (Online) 0929-5585
Published by Springer-Verlag Homepage  [2468 journals]
  • Automating functional unit and register binding for synchoros CGRA
           platform

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      Abstract: Abstract Coarse-grain reconfigurable architectures, which provide high computing throughput, low cost, scalability, and energy efficiency, have grown in popularity in recent years. SiLago is a new VLSI design framework comprised of two coarse-grain reconfigurable fabrics: a dynamically reconfigurable resource array and a distributed memory architecture. It employs the Vesyla compiler to map streaming applications on these fabrics. Binding is a critical step in the high-level synthesis that maps operations and variables to functional units and storage elements in the design. It influences design performance metrics such as power, latency, area, etc. The current version of Vesyla does not support automatic binding, and it has to be specified manually through pragmas, which makes it less flexible. This paper proposes various approaches to automate the binding in Vesyla. We present a list scheduling-based approach to automate functional unit binding and an integer linear programming approach to automate register binding. Furthermore, we determine the binding of various basic linear algebraic subprogram and image processing tasks using the proposed approaches. Finally, a comparative analysis has been made between the automatic and manual binding concerning the power dissipation and latency for various benchmarks. The experimental results show that the proposed automatic binding consumes significantly less power for nearly the same latency as manual binding.
      PubDate: 2024-06-12
       
  • Design and analysis of an adaptive radiation resilient RRAM subsystem for
           processing systems in satellites

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      Abstract: Abstract Among the numerous benefits that novel RRAM devices offer over conventional memory technologies is an inherent resilience to the effects of radiation. Hence, they appear suitable for use as a memory subsystem in a computer architecture for satellites. In addition to memory devices resistant to radiation, the concept of applying protective measures dynamically promises a system with low susceptibility to errors during radiation events, while also ensuring efficient performance in the absence of radiation events. This paper presents the first RRAM-based memory subsystem for satellites with a dynamic response to radiation events. We integrate this subsystem into a computing platform that employs the same dynamic principles for its processing system and implements modules for timely detection and even prediction of radiation events. To determine which protection mechanism is optimal, we examine various approaches and simulate the probability of errors in memory. Additionally, we are studying the impact on the overall system by investigating different software algorithms and their radiation robustness requirements using a fault injection simulation. Finally, we propose a potential implementation of the dynamic RRAM-based memory subsystem that includes different levels of protection and can be used for real applications in satellites.
      PubDate: 2024-04-10
      DOI: 10.1007/s10617-024-09285-z
       
  • Improving edge AI for industrial IoT applications with distributed
           learning using consensus

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      Abstract: Abstract Internet of Things (IoT) devices produce massive amounts of data in a very short time. Transferring these data to the cloud to be analyzed may be prohibitive for applications that require near real-time processing. One solution to meet such timing requirements is to bring most data processing closer to IoT devices (i.e., to the edge). In this context, the present work proposes a distributed architecture that meets the timing requirements imposed by Industrial IoT (IIoT) applications that need to apply Machine Learning (ML) models with high accuracy and low latency. This is done by dividing the tasks of storing and processing data into different layers—mist, fog, and cloud—using the cloud layer only for the tasks related to long-term storage of summarized data and hosting of necessary reports and dashboards. The proposed architecture employs ML inferences in the edge layer in a distributed fashion, where each edge node is either responsible for applying a different ML technique or the same technique but with a different training data set. Then, a consensus algorithm takes the ML inference results from the edge nodes to decide the result of the inference, thus improving the system’s overall accuracy. Results obtained with two different data sets show that the proposed approach can improve the accuracy of the ML models without significantly compromising the response time.
      PubDate: 2024-04-09
      DOI: 10.1007/s10617-024-09284-0
       
  • Novel adaptive quantization methodology for 8-bit floating-point DNN
           training

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      Abstract: Abstract There is a high energy cost associated with training Deep Neural Networks (DNNs). Off-chip memory access contributes a major portion to the overall energy consumption. Reduction in the number of off-chip memory transactions can be achieved by quantizing the data words to low data bit-width (E.g., 8-bit). However, low-bit-width data formats suffer from a limited dynamic range, resulting in reduced accuracy. In this paper, a novel 8-bit Floating Point (FP8) data format quantized DNN training methodology is presented, which adapts to the required dynamic range on-the-fly. Our methodology relies on varying the bias values of FP8 format to fit the dynamic range to the required range of DNN parameters and input feature maps. The range fitting during the training is adaptively performed by an online statistical analysis hardware unit without stalling the computation units or its data accesses. Our approach is compatible with any DNN compute cores without any major modifications to the architecture. We propose to integrate the new FP8 quantization unit in the memory controller. The FP32 data from the compute core are converted to FP8 in the memory controller before writing to the DRAM and converted back after reading the data from DRAM. Our results show that the DRAM access energy is reduced by 3.07 \(\times \) while using an 8-bit data format instead of using 32-bit. The accuracy loss of the proposed methodology with 8-bit quantized training is \(\approx 1\%\) for various networks with image and natural language processing datasets.
      PubDate: 2024-02-16
      DOI: 10.1007/s10617-024-09282-2
       
  • Profiling with trust: system monitoring from trusted execution
           environments

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      Abstract: Abstract Large-scale attacks on IoT and edge computing devices pose a significant threat. As a prominent example, Mirai is an IoT botnet with 600,000 infected devices around the globe, capable of conducting effective and targeted DDoS attacks on (critical) infrastructure. Driven by the substantial impacts of attacks, manufacturers and system integrators propose Trusted Execution Environments (TEEs) that have gained significant importance recently. TEEs offer an execution environment to run small portions of code isolated from the rest of the system, even if the operating system is compromised. In this publication, we examine TEEs in the context of system monitoring and introduce the Trusted Monitor (TM), a novel anomaly detection system that runs within a TEE. The TM continuously profiles the system using hardware performance counters and utilizes an application-specific machine-learning model for anomaly detection. In our evaluation, we demonstrate that the TM accurately classifies 86% of 183 tested workloads, with an overhead of less than 2%. Notably, we show that a real-world kernel-level rootkit has observable effects on performance counters, allowing the TM to detect it. Major parts of the TM are implemented in the Rust programming language, eliminating common security-critical programming errors.
      PubDate: 2024-02-16
      DOI: 10.1007/s10617-024-09283-1
       
  • Transparent integration of autonomous vehicles simulation tools with a
           data-centric middleware

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      Abstract: Abstract Simulations are key steps in the design, implementation, and verification of autonomous vehicles (AV). Parallel to this, typical simulation tools fail to integrate the entirety of the aspects related to the complexity of AV applications, such as data communication delay, security, and the integration of software/hardware-in-the-loop and other simulation tools. This work proposes a SmartData-based middleware to integrate AV simulators and external tools. The interface models the data used on a simulator and creates an intermediary layer between the simulator and the external tools by defining the inputs and outputs as SmartData. A message bus is used for communication between SmartData following their Interest relations. Messages are exchanged following a specific protocol. Nevertheless, the architecture presented is agnostic of protocol. Moreover, we present a data-centric AV design integrated into the middleware. The design considers the standardization of the data interfaces between AV components, including sensing, perception, planning, decision, and actuation. Therefore, the presented design promotes a transparent integration of the AV simulation with other simulators (e.g., network simulators), cloud services, fault injection mechanisms, digital twins, and hardware-in-the-loop scenarios. Moreover, the design allows for transparent, runtime component replacement and time synchronization, the modularization of the vehicle components, and the addition of security aspects in the simulation. We present a case-study application with an AV simulation using CARLA, and we measure the end-to-end delay and overhead incurred in the simulation by our middleware. An increase in the end-to-end delay was measured once data communication was not acknowledged in the original scenario, and data was assumed to be ready for processing with no communication delay between sensors, decision-making, and actuation units.
      PubDate: 2024-01-06
      DOI: 10.1007/s10617-023-09280-w
       
  • On the impact of hardware-related events on the execution of real-time
           programs

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      Abstract: Abstract Estimating safe upper bounds on execution times of programs is required in the design of predictable real-time systems. When multi-core, instruction pipeline, branch prediction, or cache memory are in place, due to the considerable complexity traditional static timing analysis faces, measurement-based timing analysis (MBTA) is a more tractable option. MBTA estimates upper bounds on execution times using data measured under the execution of representative execution scenarios. In this context, understanding how hardware-related events affect the executing program under analysis brings about useful information for MBTA. This paper contributes to this need by modeling the execution behavior of programs in function of hardware-related events. More specifically, for a program under analysis, we show that the number of cycles per executed instruction can be correlated to hardware-related event occurrences. We apply our modeling methodology to two architectures, ARMv7 Cortex-M4 and Cortex-A53. While all hardware events can be monitored at once in the former, the latter allows simultaneous monitoring of up to 6 out of 59 events. We then describe a method to select the most relevant hardware events that affect the execution of a program under analysis. These events are then used to model the program behavior via machine learning techniques under different execution scenarios. The effectiveness of this method is evaluated by extensive experiments. Obtained results revealed prediction errors below 20%, showing that the chosen events can largely explain the execution behavior of programs.
      PubDate: 2023-12-31
      DOI: 10.1007/s10617-023-09281-9
       
  • Multiprovision: a Design Space Exploration tool for multi-tenant resource
           provisioning in CPU–GPU environments

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      Abstract: Abstract Cloud warehouses are increasingly adopting CPU–GPU collaborative systems to leverage diverse types and levels of parallelism in applications. These environments are shared among multiple clients to achieve maximum resource utilization with energyf efficiency and scalability. While OpenCL simplifies resource provisioning in such heterogeneous systems, ensuring the effective distribution of tasks remains challenging as CPU–GPU available architectures and workload characteristics can vary significantly. This study addresses the challenge of efficiently provisioning resources in OpenCL-based CPU–GPU cloud environments. To tackle this challenge, we introduce MultiProvision, a Design Space Exploration tool for multi-tenant resource provisioning in CPU–GPU environments. MultiProvision facilitates the identification of the most suitable provisioning strategy for a given workload and architecture scenario in a transparent manner. Through comprehensive evaluations encompassing various architecture combinations and workloads, we demonstrate that the choice of the most efficient provisioning strategy depends on the target architecture, workload characteristics, and optimization objectives, such as makespan or energy. We show that the appropriate strategy can achieve remarkable gains of up to 13.15 \(\times \) in makespan and 4.52 \(\times \) in energy compared to a GPU-only execution.
      PubDate: 2023-12-21
      DOI: 10.1007/s10617-023-09279-3
       
  • Monitoring the performance of multicore embedded systems without
           disrupting its timing requirements

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      Abstract: Abstract Monitoring the performance of multicore embedded systems is crucial to properly ensure their timing requirements. Collecting performance data is also very relevant for optimization and validation efforts. However, the strategies used to monitor and capture data in such systems are complex to design and implement since they must not interfere with the running system beyond the point at which the system’s timing and performance characteristics start to get affected by the monitoring strategies. In this paper, we extend a monitoring framework developed in previous work to encompass three monitoring strategies, namely Active and Passive Periodic monitoring and Job-based monitoring. Periodic monitoring follows a given sampling rate. Active Periodic relies on periodic timer interrupts to guarantee deterministic sampling, while Passive Periodic trades determinism for a less invasive strategy, sampling data only when ordinary system events are handled. Job-based follows an event-driven monitoring that samples data whenever a job leaves the CPU, thus building isolated traces for each job. We evaluate them according to overhead, latency, and jitter, where none of them presented an average impact on the system execution time higher than \(0.3\%\) . Moreover, a qualitative analysis is conducted in terms of data quality. On one hand, while Periodic monitoring allows for configurable sampling rates, it does not account for the rescheduling of jobs and may capture mixed traces. On the other hand, Job-based monitoring provides data samples tied to the execution of each job while disregarding sampling rate configuration and may lose track of instant measures.
      PubDate: 2023-12-16
      DOI: 10.1007/s10617-023-09278-4
       
  • On vulnerabilities in EVT-based timing analysis: an experimental
           investigation on a multi-core architecture

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      Abstract: Abstract Hardware architectures based on multiple cores, cache memory and branch prediction usually preclude the application of classical methods for determining execution time bounds for real-time tasks. As such bounds are fundamental in the designing of real-time systems, Measurement-Based Probabilistic Timing Analysis has been employed. A common choice is the derivation of probabilistic Worst-Case Execution Time via the use of Extreme Value Theory, a branch of statistics used to estimate the probability of rare events that are more extreme than observations. However, pWCET estimations are usually reported in a controlled or simulated environment. In this paper we apply MBPTA in a real multi-core platform, namely Raspberry Pi 3B, taking into consideration possible interference due to operating system and concurrent activities. The results indicate that although EVT is effective, it does not always produce adequate models and coherent pWCET estimations. As MBPTA is primarily called for when classical methods are not applicable, as it is the case for the studied platform, the results reported in this paper highlight risks and vulnerabilities when applying MBPTA-EVT for pWCET inference.
      PubDate: 2023-10-17
      DOI: 10.1007/s10617-023-09277-5
       
  • Special issue with selected Papers from 2020 brazilian symposium on
           computer engineering (SBESC 2020)

    • Free pre-print version: Loading...

      PubDate: 2023-06-20
      DOI: 10.1007/s10617-023-09275-7
       
  • Hardware-accelerated service-oriented communication for AUTOSAR platforms

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      Abstract: Abstract With the evolving complexity in automotive software in the last decade, a need for optimized custom hardware to support basic common functions is rising. AUTOSAR consortium defines a standard software specification for automotive software. A so-called SOME/IP (Scalable service-Oriented MiddlewarE over IP) transformer is one of these defined standard specifications. SOME/IP transformer is widely used in Ethernet-connected AUTOSAR-based Electronic Control Units for its scalability that is needed to cope with the increased optional features in today’s automotive software. In this paper, we propose a custom hardware support to accelerate one of the SOME/IP transformer functions, studying its overhead, limitations, and performance gain. Using our proposed solution, we achieved \(50\times \) speedup over of the traditional software implementation. The proposed hardware design maintains the same simplicity, flexibility, and modularity offered by traditional software solutions with minimal added overhead. Having a dedicated hardware for SOME/IP transformation makes the overall architecture more reliable.
      PubDate: 2023-06-13
      DOI: 10.1007/s10617-023-09276-6
       
  • Efficient placement and migration policies for an STT-RAM based hybrid L1
           cache for intermittently powered systems

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      Abstract: Abstract The number of battery-powered devices is rapidly increasing due to the widespread use of IoT-enabled nodes in various fields. Energy harvesters, which help to power embedded devices, are a feasible alternative to replacing battery-powered devices. In a capacitor, the energy harvester stores enough energy to power up the embedded device and compute the task. This type of computation is referred to as intermittent computing. Energy harvesters are unable to supply continuous power to embedded devices. All registers and cache in conventional processors are volatile. We require a Non-Volatile Memory (NVM)-based Non-Volatile Processor (NVP) that can store registers and cache contents during a power failure. NVM-based caches reduce system performance and consume more energy than SRAM-based caches. This paper proposes Efficient Placement and Migration policies for hybrid cache architecture that uses SRAM and STT-RAM at the first level cache. The proposed architecture includes cache block placement and migration policies to reduce the number of writes to STT-RAM. During a power failure, the backup strategy identifies and migrates the critical blocks from SRAM to STT-RAM. When compared to the baseline architecture, the proposed architecture reduces STT-RAM writes from 63.35% to 35.93%, resulting in a 32.85% performance gain and a 23.42% reduction in energy consumption. Our backup strategy reduces backup time by 34.46% when compared to the baseline.
      PubDate: 2023-05-05
      DOI: 10.1007/s10617-023-09272-w
       
  • Accelerated and optimized covariance descriptor for pedestrian detection
           in self-driving cars

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      Abstract: Abstract Self-Driving vehicles are expected to thrive in the coming years. These vehicles are designed to analyze the environment around them in real-time to identify obstacles and hazards. One of the most important aspects of designing a self-driving vehicle is to preserve the safety of pedestrians. This requires accurate and rapid pedestrian detection, which is a key operation in various other applications including video surveillance and assisted living. The covariance descriptor is one of the most efficient descriptors used in detecting pedestrians. However, the descriptor is compute-intensive; rendering it less favorable for real-time applications. This paper proposes an accelerated and optimized implementation of the descriptor. Instead of mapping the entire descriptor to a hardware accelerator, we opt for a heterogeneous architecture. In particular, compute-intensive components of the descriptor are accelerated on hardware, while the other components are executed on an embedded processor. The proposed architecture combines both speed and flexibility while being watchful of precious hardware resources. This architecture was validated on a Zynq SoC platform, which hosts FPGA fabric along with an ARM processor. The results of executing the descriptor on the platforms show a performance gain of up to 13.52 × when compared to pure software implementation of the descriptor.
      PubDate: 2023-04-28
      DOI: 10.1007/s10617-023-09273-9
       
  • A high-speed reusable quantized hardware accelerator design for CNN on
           constrained edge device

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      Abstract: Abstract The most recent deep learning technique used in many applications is the convolutional neural network (CNN). Recent years have seen a rise in demand for real-time CNN implementations on various embedded devices with restricted resources. The CNN models should be implemented using field-programmable gate arrays to ensure flexible programmability and speed up the development process. However, the CNN acceleration is hampered by complex computations, limited bandwidth, and on-chip memory storage. In this paper, a reusable quantized hardware architecture was proposed to accelerate deep CNN models by solving the above issues. Twenty-five processing elements are employed for the computation of convolutions in the CNN model. Pipelining, loop unrolling, and array partitioning are the techniques for increasing the speed of computations in both the convolution layers and fully connected layers. This design is tested with MNIST handwritten digit image classification on a low-cost, low-memory Xilinx PYNQ-Z2 system on chip edge device. The inference speed of the proposed hardware design achieved 92.7% higher than INTEL core3 CPU, 90.7% more than Haswell core2 CPU, 87.7% more than NVIDIA Tesla K80 GPU, and 84.9% better when compared to the conventional hardware accelerator with one processing element. The proposed quantized architecture design has achieved the performance of 4.4 GOP/s without compromising the accuracy and it was 2 times more than the conventional architecture.
      PubDate: 2023-04-26
      DOI: 10.1007/s10617-023-09274-8
       
  • Predictable timing behavior of gracefully degrading automotive systems

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      Abstract: Abstract Fail-operational behavior of safety-critical software for autonomous driving is essential as there is no driver available as a backup solution. In a failure scenario, safety-critical tasks can be restarted on other available hardware resources. Here, graceful degradation can be used as a cost-efficient solution where hardware resources are redistributed from non-critical to safety-critical tasks at run-time. We allow non-critical tasks to actively use resources that are reserved as a backup for critical tasks, which would be otherwise unused and which are only required in a failure scenario. However, in such a scenario, it is of paramount importance to achieve a predictable timing behavior of safety-critical applications to allow a safe operation. Here, it has to be ensured that even after the restart of safety-critical tasks a guarantee on execution times can be given. In this paper, we propose a graceful degradation approach using composable scheduling. We use our approach to present, for the first time, a performance analysis which is able to analyze timing constraints of fail-operational distributed applications using graceful degradation. Our method can verify that even during a critical Electronic Control Unit failure, there is always a backup solution available which adheres to end-to-end timing constraints. Furthermore, we present a dynamic decentralized mapping procedure which performs constraint solving at run-time using our analytical approach combined with a backtracking algorithm. We evaluate our approach by comparing mapping success rates to state-of-the-art approaches such as active redundancy and an approach based on resource availability. In our experimental setup our graceful degradation approach can fit about double the number of critical applications on the same architecture compared to an active redundancy approach. Combined, our approaches enable, for the first time, a dynamic and fail-operational behavior of gracefully degrading automotive systems with cost-efficient backup solutions for safety-critical applications.
      PubDate: 2023-04-11
      DOI: 10.1007/s10617-023-09271-x
       
  • Low-cost modular devices for on-road vehicle detection and
           characterisation

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      Abstract: Abstract Detecting and characterising vehicles is one of the purposes of embedded systems used in intelligent environments. An analysis of a vehicle’s characteristics can reveal inappropriate or dangerous behaviour. This detection makes it possible to sanction or notify emergency services to take early and practical actions. Vehicle detection and characterisation systems employ complex sensors such as video cameras, especially in urban environments. These sensors provide high precision and performance, although the price and computational requirements are proportional to their accuracy. These sensors offer high accuracy, but the price and computational requirements are directly proportional to their performance. This article introduces a system based on modular devices that is economical and has a low computational cost. These devices use ultrasonic sensors to detect the speed and length of vehicles. The measurement accuracy is improved through the collaboration of the device modules. The experiments were performed using multiple modules oriented to different angles. This module is coupled with another specifically designed to detect distance using previous modules’ speed and length data. The collaboration between different modules reduces the speed relative error ranges from 1 to 5%, depending on the angle configuration used in the modules.
      PubDate: 2023-04-07
      DOI: 10.1007/s10617-023-09270-y
       
  • Scheduling and energy savings for small scale embedded FreeRTOS-based
           real-time systems

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      Abstract: Abstract Evaluating the effectiveness of system scheduling and energy savings in embedded real-time systems with low-computing resources is the problem addressed in this paper. In such systems, the characteristics of the implemented scheduling policy play a relevant role in both schedulability and energy consumption. Ideally, the scheduling policy should provide higher schedulability bounds and low runtime overheads, allowing for better usage of available slack in the schedule for energy saving purposes. Due its low overhead and simple implementation, the usual scheduling policy employed in real-time embedded systems is based on fixed priority scheduling (FPS). Under this scheme, as the priority of all system tasks are assigned at design time, a simple priority vector suffices to indicate the current ready task to run. System schedulability, however, is usually lower than that provided by dynamic priority scheduling (DPS) according to which task priorities are assigned at runtime. Managing dynamic priority queues incurs higher overheads, though. Deciding whether DPS is a viable choice for such embedded systems requires careful evaluation. We evaluate two implementations of Earliest Deadline First (EDF), a classical DPS policy, implemented in FreeRTOS running on an ARM-M4 architecture. EDF is compared against an optimal FPS, namely Rate-Monotonic (RM). Further, two mechanisms for energy savings are described. They differ by the manner they compute the slack available in an EDF schedule, statically (SS-EDF) or dynamically (DS-EDF). These two approaches are experimentally evaluated. Results indicate that EDF can be effectively used for energy savings.
      PubDate: 2023-03-15
      DOI: 10.1007/s10617-023-09267-7
       
  • Using evolutionary metaheuristics to solve the mapping and routing problem
           in networks on chip

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      Abstract: Abstract Task mapping and routing are crucial steps in the Networks on Chip (NoC) based Multiprocessor System on Chip (MPSoC) design. While the mapping must ensure an optimized arrangement of the applications’ tasks on the system cores, the routing must ensure the tasks’ communication with the minimum possible delay. We observe that these two problems are highly dependent since finding a routing solution requires first finding a mapping solution. Based on that, this paper analyzes the mapping and routing problems in NoC-based MPSoC and defines a joint version as the Mapping and Routing Problem (MRP). We propose a mathematical model that generates mapping and routing solutions based on a specific bandwidth of NoC links. We also propose three evolutionary metaheuristic algorithms to find optimized solutions to the MRP: Genetic (GA), Memetic (MA), and Transgenetic Algorithms (TA). Experimental results evaluating communication latency demonstrate that the proposed algorithms suit well for the tackled problem, but the TA stands out among all the compared solutions. Overall, TA achieved up to 8% and 19% better performance than the compared algorithms in Global Average Delay and Maximum Delay. Also, it outperformed the other strategies in 55.76% and 51.58% of all the performed simulations in both respective metrics.
      PubDate: 2023-03-10
      DOI: 10.1007/s10617-023-09269-5
       
  • Supporting single and multi-core resource access protocols on
           object-oriented RTOSes

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      Abstract: Abstract Real-time resource access protocols are fundamental to bound the maximum delay a task can suffer due to priority inversions. Several real-time protocols have been proposed, for both static and dynamic scheduling approaches in single and multi-core processors. One of the main factors for performance efficiency in such protocols is the way they are implement within a real-time operating system (RTOS). In this paper we present an object-oriented design of real-time access protocols considering single and multi-core systems and also suspension- and spin-based protocols (7 protocols in total). Our design aims at reducing the run-time overhead and increasing code re-usability. By implementing the proposed design in an RTOS and running the protocols in a modern multi-core processor, we provide an analysis regarding the memory footprint, run-time overhead, and the impact of the overhead into the schedulability analysis of synthetically generated task sets. Our results indicate that proper implementation provides low run-time overhead (up to 6.1  \(\upmu \hbox {s}\) ) and impact on the schedulability of real-time tasks.
      PubDate: 2023-03-01
      DOI: 10.1007/s10617-023-09268-6
       
 
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  Subjects -> COMPUTER SCIENCE (Total: 2313 journals)
    - ANIMATION AND SIMULATION (33 journals)
    - ARTIFICIAL INTELLIGENCE (133 journals)
    - AUTOMATION AND ROBOTICS (116 journals)
    - CLOUD COMPUTING AND NETWORKS (75 journals)
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    - COMPUTER SCIENCE (1305 journals)
    - COMPUTER SECURITY (59 journals)
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    - E-BUSINESS (21 journals)
    - E-LEARNING (30 journals)
    - ELECTRONIC DATA PROCESSING (23 journals)
    - IMAGE AND VIDEO PROCESSING (42 journals)
    - INFORMATION SYSTEMS (109 journals)
    - INTERNET (111 journals)
    - SOCIAL WEB (61 journals)
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    - THEORY OF COMPUTING (10 journals)

AUTOMATION AND ROBOTICS (116 journals)                     

Showing 1 - 101 of 101 Journals sorted alphabetically
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 10)
ACM Transactions on Human-Robot Interaction     Open Access   (Followers: 4)
Advanced Robotics     Hybrid Journal   (Followers: 29)
Advances in Computed Tomography     Open Access   (Followers: 2)
Advances in Image and Video Processing     Open Access   (Followers: 27)
Advances in Robotics & Automation     Open Access   (Followers: 12)
Artificial Life and Robotics     Hybrid Journal   (Followers: 17)
Augmented Human Research     Hybrid Journal  
Automated Software Engineering     Hybrid Journal   (Followers: 9)
Automatic Control and Information Sciences     Open Access   (Followers: 4)
Automation and Remote Control     Hybrid Journal   (Followers: 6)
Autonomous Agents and Multi-Agent Systems     Hybrid Journal   (Followers: 9)
Autonomous Robots     Hybrid Journal   (Followers: 11)
Biocybernetics and Biological Engineering     Full-text available via subscription   (Followers: 4)
Biological Cybernetics     Hybrid Journal   (Followers: 10)
Biomimetic Intelligence and Robotics     Open Access  
Cognitive Robotics     Open Access   (Followers: 4)
Computational Intelligence and Neuroscience     Open Access   (Followers: 18)
Computer-Aided Design     Hybrid Journal   (Followers: 9)
Construction Robotics     Hybrid Journal   (Followers: 5)
Current Robotics Reports     Hybrid Journal   (Followers: 4)
Cybernetics & Human Knowing     Full-text available via subscription   (Followers: 3)
Cybernetics and Systems Analysis     Hybrid Journal  
Cybernetics and Systems: An International Journal     Hybrid Journal   (Followers: 1)
Design Automation for Embedded Systems     Hybrid Journal   (Followers: 4)
Digital Zone : Jurnal Teknologi Informasi Dan Komunikasi     Open Access  
Drone Systems and Applications     Open Access   (Followers: 1)
Electrical Engineering and Automation     Open Access   (Followers: 9)
Facta Universitatis, Series : Automatic Control and Robotics     Open Access   (Followers: 1)
Foundations and Trends® in Robotics     Full-text available via subscription   (Followers: 4)
GIScience & Remote Sensing     Open Access   (Followers: 58)
IAES International Journal of Robotics and Automation     Open Access   (Followers: 5)
IEEE Robotics & Automation Magazine     Full-text available via subscription   (Followers: 69)
IEEE Robotics and Automation Letters     Hybrid Journal   (Followers: 9)
IEEE Transactions on Affective Computing     Hybrid Journal   (Followers: 23)
IEEE Transactions on Audio, Speech, and Language Processing     Hybrid Journal   (Followers: 17)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 70)
IEEE Transactions on Cybernetics     Hybrid Journal   (Followers: 16)
IEEE Transactions on Intelligent Vehicles     Hybrid Journal   (Followers: 2)
IEEE Transactions on Medical Robotics and Bionics     Hybrid Journal   (Followers: 5)
IEEE Transactions on Neural Networks and Learning Systems     Hybrid Journal   (Followers: 57)
IEEE Transactions on Robotics     Hybrid Journal   (Followers: 71)
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews     Hybrid Journal   (Followers: 16)
IET Cyber-systems and Robotics     Open Access   (Followers: 2)
IET Systems Biology     Open Access   (Followers: 1)
Industrial Robot An International Journal     Hybrid Journal   (Followers: 2)
Intelligent Control and Automation     Open Access   (Followers: 6)
Intelligent Service Robotics     Hybrid Journal   (Followers: 2)
International Journal of Adaptive, Resilient and Autonomic Systems     Full-text available via subscription   (Followers: 3)
International Journal of Advanced Pervasive and Ubiquitous Computing     Full-text available via subscription   (Followers: 4)
International Journal of Advanced Robotic Systems     Full-text available via subscription   (Followers: 1)
International Journal of Agent Technologies and Systems     Full-text available via subscription   (Followers: 4)
International Journal of Ambient Computing and Intelligence     Full-text available via subscription   (Followers: 3)
International Journal of Applied Evolutionary Computation     Full-text available via subscription   (Followers: 3)
International Journal of Artificial Life Research     Full-text available via subscription  
International Journal of Automation and Control     Hybrid Journal   (Followers: 11)
International Journal of Automation and Control Engineering     Open Access   (Followers: 5)
International Journal of Automation and Logistics     Hybrid Journal   (Followers: 4)
International Journal of Automation and Smart Technology     Open Access   (Followers: 3)
International Journal of Bioinformatics Research and Applications     Hybrid Journal   (Followers: 14)
International Journal of Biomechatronics and Biomedical Robotics     Hybrid Journal   (Followers: 2)
International Journal of Humanoid Robotics     Hybrid Journal   (Followers: 6)
International Journal of Imaging & Robotics     Full-text available via subscription   (Followers: 3)
International Journal of Intelligent Information Technologies     Full-text available via subscription   (Followers: 1)
International Journal of Intelligent Machines and Robotics     Hybrid Journal   (Followers: 3)
International Journal of Intelligent Mechatronics and Robotics     Full-text available via subscription   (Followers: 5)
International Journal of Intelligent Robotics and Applications     Hybrid Journal  
International Journal of Intelligent Systems Design and Computing     Hybrid Journal   (Followers: 2)
International Journal of Intelligent Unmanned Systems     Hybrid Journal   (Followers: 3)
International Journal of Machine Consciousness     Hybrid Journal   (Followers: 7)
International Journal of Machine Learning and Cybernetics     Hybrid Journal   (Followers: 31)
International Journal of Mechanisms and Robotic Systems     Hybrid Journal   (Followers: 2)
International Journal of Mechatronics and Automation     Hybrid Journal   (Followers: 5)
International Journal of Robotics and Automation     Full-text available via subscription   (Followers: 8)
International Journal of Robotics and Control     Open Access   (Followers: 3)
International Journal of Robotics Applications and Technologies     Full-text available via subscription   (Followers: 1)
International Journal of Robotics Research     Hybrid Journal   (Followers: 15)
International Journal of Space-Based and Situated Computing     Hybrid Journal   (Followers: 2)
International Journal of Synthetic Emotions     Full-text available via subscription  
International Journal of Tomography & Simulation     Full-text available via subscription   (Followers: 1)
Journal of Automation and Control     Open Access   (Followers: 9)
Journal of Computer Assisted Tomography     Hybrid Journal   (Followers: 2)
Journal of Control & Instrumentation     Full-text available via subscription   (Followers: 19)
Journal of Control, Automation and Electrical Systems     Hybrid Journal   (Followers: 11)
Journal of Intelligent and Robotic Systems     Hybrid Journal   (Followers: 6)
Journal of Intelligent Learning Systems and Applications     Open Access   (Followers: 4)
Journal of Robotic Surgery     Hybrid Journal   (Followers: 3)
Jurnal Otomasi Kontrol dan Instrumentasi     Open Access  
Machine Translation     Hybrid Journal   (Followers: 12)
Proceedings of the ACM on Human-Computer Interaction     Hybrid Journal   (Followers: 2)
Results in Control and Optimization     Open Access   (Followers: 5)
Revista Iberoamericana de Automática e Informática Industrial RIAI     Open Access  
ROBOMECH Journal     Open Access   (Followers: 1)
Robotic Surgery : Research and Reviews     Open Access   (Followers: 1)
Robotica     Hybrid Journal   (Followers: 5)
Robotics and Autonomous Systems     Hybrid Journal   (Followers: 19)
Robotics and Biomimetics     Open Access   (Followers: 1)
Robotics and Computer-Integrated Manufacturing     Hybrid Journal   (Followers: 7)
Science Robotics     Full-text available via subscription   (Followers: 11)
Unmanned Systems     Hybrid Journal   (Followers: 4)
Wearable Technologies     Open Access   (Followers: 4)

           

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School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


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