540 research outputs found
Multi-tone EMC testing strategy for RF-devices
In low-cost miniaturized electronic systems, filters are often omitted in front of active non-linear components, potentially resulting in unwanted intermodulation products in the band of operation. Current immunity tests most often use a single-frequency source and are hence not able to capture all relevant intermodulation products. Relying on an anechoic chamber as test facility and using multiple-tone excitation from a dual-source network analyzer, we present an advanced test methodology to evaluate in-the-band leakage of out-of-band undesired frequencies. To demonstrate our approach we use a frequency-selective active textile antenna with integrated non-linear low-noise amplifier
Electromagnetic compatibility aware design and testing of intermodulation distortion under multiple co-located sources illumination
Current electromagnetic immunity tests mainly rely on single-frequency sources. However, the evolution of electronic systems leads to miniaturisation and low-cost solutions, in which filters are omitted in front of active non-linear components, also for efficiency reasons. As a result, intermodulation products may leak into the band of operation. The authors propose a comprehensive strategy consisting of design and test methodologies to evaluate in-the-band leakage of out-of-band undesired components, using multiple-tone excitation and relying on an anechoic chamber as test facility. The aim of this study is to demonstrate that an anechoic chamber together with a dual-source network analyser represents an optimal facility to investigate signal integrity issues owing to leakage of intermodulation products
Variability analysis of interconnect structures including general nonlinear elements in SPICE-type framework
A stochastic modelling method is developed and implemented in a SPICE framework to analyse variability effects on interconnect structures including general nonlinear element
The SRP Resource Sharing Protocol for Self-Suspending Tasks
Motivated by the increasingly wide adoption of realtime workload with self-suspending behaviors, and the relevance of mechanisms to handle mutually-exclusive shared resources, this paper takes a new look at locking protocols for self-suspending tasks under uniprocessor fixed-priority scheduling. Pitfalls when integrating the widely-adopted Stack Resource Policy (SRP) with self-suspending tasks are firstly illustrated, and then a new finegrained SRP analysis is presented. Next, a new locking protocol, named SRP-SS, is proposed to overcome the limitations of the original SRP. The SRP-SS is a generalization of the SRP to cope with the specificities of self-suspending tasks. It therefore reduces to the SRP under some configurations and hence theoretically dominates the SRP. It also ensures backward compatibility for applications developed specifically for the SRP. The SRP-SS comes with its own schedulability analysis and configuration algorithm. The performances of the SRP and SRP-SS are finally studied by means of large-scale schedulability experiments.info:eu-repo/semantics/publishedVersio
Semi-Partitioned Scheduling of Dynamic Real-Time Workload: A Practical Approach Based on Analysis-Driven Load Balancing
Recent work showed that semi-partitioned scheduling can achieve near-optimal schedulability performance, is simpler to implement compared to global scheduling, and less heavier in terms of runtime overhead, thus resulting in an excellent choice for implementing real-world systems. However, semi-partitioned scheduling typically leverages an off-line design to allocate tasks across the available processors, which requires a-priori knowledge of the workload. Conversely, several simple global schedulers, as global earliest-deadline first (G-EDF), can transparently support dynamic workload without requiring a task-allocation phase. Nonetheless, such schedulers exhibit poor worst-case performance. This work proposes a semi-partitioned approach to efficiently schedule dynamic real-time workload on a multiprocessor system. A linear-time approximation for the C=D splitting scheme under partitioned EDF scheduling is first presented to reduce the complexity of online scheduling decisions. Then, a load-balancing algorithm is proposed for admitting new real-time workload in the system with limited workload re-allocation. A large-scale experimental study shows that the linear-time approximation has a very limited utilization loss compared to the exact technique and the proposed approach achieves very high schedulability performance, with a consistent improvement on G-EDF and pure partitioned EDF scheduling
Semi-Partitioned Scheduling of Dynamic Real-Time Workload: A Practical Approach Based on Analysis-Driven Load Balancing
Recent work showed that semi-partitioned scheduling can achieve near-optimal schedulability performance, is simpler to implement compared to global scheduling, and less heavier in terms of runtime overhead, thus resulting in an excellent choice for implementing real-world systems. However, semi-partitioned scheduling typically leverages an off-line design to allocate tasks across the available processors, which requires a-priori knowledge of the workload. Conversely, several simple global schedulers, as global earliest-deadline first (G-EDF), can transparently support dynamic workload without requiring a task-allocation phase. Nonetheless, such schedulers exhibit poor worst-case performance.
This work proposes a semi-partitioned approach to efficiently schedule dynamic real-time workload on a multiprocessor system. A linear-time approximation for the C=D splitting scheme under partitioned EDF scheduling is first presented to reduce the complexity of online scheduling decisions. Then, a load-balancing algorithm is proposed for admitting new real-time workload in the system with limited workload re-allocation. A large-scale experimental study shows that the linear-time approximation has a very limited utilization loss compared to the exact technique and the proposed approach achieves very high schedulability performance, with a consistent improvement on G-EDF and pure partitioned EDF scheduling
Increasing the Confidence of Deep Neural Networks by Coverage Analysis
The great performance of machine learning algorithms and deep neural networks
in several perception and control tasks is pushing the industry to adopt such
technologies in safety-critical applications, as autonomous robots and
self-driving vehicles. At present, however, several issues need to be solved to
make deep learning methods more trustworthy, predictable, safe, and secure
against adversarial attacks. Although several methods have been proposed to
improve the trustworthiness of deep neural networks, most of them are tailored
for specific classes of adversarial examples, hence failing to detect other
corner cases or unsafe inputs that heavily deviate from the training samples.
This paper presents a lightweight monitoring architecture based on coverage
paradigms to enhance the model robustness against different unsafe inputs. In
particular, four coverage analysis methods are proposed and tested in the
architecture for evaluating multiple detection logics. Experimental results
show that the proposed approach is effective in detecting both powerful
adversarial examples and out-of-distribution inputs, introducing limited
extra-execution time and memory requirements
Scheduling Replica Voting in Fixed-Priority Real-Time Systems
Reliability and safety are mandatory requirements for safety-critical embedded systems. The design of a fault-tolerant system is required in many fields (e.g., railway, automotive, avionics) and redundancy helps in achieving this goal. Redundant systems typically leverage voting techniques applied to the outputs produced by tasks to detect and even tolerate failures.
This paper studies the integration of distributed voting protocols in fixed-priority real-time systems from a scheduling perspective. It analyzes two scheduling strategies for implementing voting. One is attractive and friendly for software developers and based on suspending the task execution until the replica provides the data to be voted. The other one is inspired by the Logical Execution Time (LET) paradigm and requires introducing additional tasks in the system to accomplish voting-related activities. Queuing and delays introduced by inter-replica communication interfaces are also analyzed.
Experimental results are finally presented to compare the two strategies, showing that LET-inspired voting is much more predictable and hence more suitable than the other strategy for fixed-priority real-time systems
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