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This paper evaluates the efficiency and performance impact of a dual-core lockstep as a method for fault-tolerance running on top of FreeRTOS applications. The method was implemented on a dual-core ARM Cortez-A9 processor embedded into the Zynq-7000 APSoC. Fault injection experiments show that the method can mitigate up to 63% on the FreeRTOS applications. This result is very near to the mitigation...
This article describes approaches to building a set of nodes and blocks that are sufficient to create the matching processor for the parallel dataflow computing system. Investigations of various sets of nodes and blocks of the matching processor have been carried out. As a result, some regularities were revealed characteristic for hardware-software solutions that implement the dataflow computing model...
Nowadays, there are many embedded systems with different architectures that have incorporated GPUs. However, it is difficult to develop CPU-GPU embedded systems using component-based development (CBD), since existing CBD approaches have no support for GPU development. In this context, when targeting a particular CPU-GPU platform, the component developer is forced to construct hardware-specific components,...
Avionics systems, along with their internal hardware and software components interfaces, must be well defined and specified (e.g., unambiguous, complete, verifiable, consistent, and traceable specification). Such a specification is usually written in the form of an Interface Control Document (ICD), and represents the cornerstone of the avionics system integration activities. However, there is no commonly...
Self-adaptive systems are modern applications in which the running software system should be able to react on its own, by dynamically adapting its behavior, for sustaining a required set of qualities of service, and dynamic changes in the context or in user requirements. They are typically involved in Future Internet development such as the Internet of Things where interoperability, flexibility, and...
We target the evaluation of a Superfluid 5G network from an economic point of view. The considered 5G architecture has notably features, such as flexibility, agility, portability and high performance, as shown by the H2020 SUPERFLUIDITY project. The proposed economic model, tailored to the Superfluid network architecture, allows to compute the CAPEX, the OPEX, the Net Present Value (NPV) and the Internal...
Thanks to the appearance of the General-Purpose computing on Graphics Processing Units (GPGPU), researchers have benefited from the spectacular High Performance Computing (HPC) provided by GPUs. Different research fields, such as combinatorial optimization, have taken advantages from the GPUs HPC. In this context, our paper introduces some different Particle Swarm Optimization (PSO) implementations...
Several researches have pointed the hybridization of metaheuristics as an effective way to deal with combinatorial optimization problems. Hybridization allows the combination of different techniques, exploiting the strengths and compensating the weakness of each of them. MAHM is a promising adaptive framework for hybridization of metaheuristics, originally designed for single objective problems. This...
Aiming to keep under control a particular system or environment or to ensure that it works as expected there is a need to know what-when-why happens there. Various conditions and environmental factors can lead to errors, unexpected behavior or loss of control. To pursue these factors manually is time consuming, error prone, slow and usually quite expensive. Monitoring is quite complex and challenging...
This paper introduces a methodology to design a Context-aware Adaptive System based on a layered software architecture. The model of the context awareness multi-modal traffic management takes into account the context parameters in order to adapt dynamically the decisions (choice of the best transportation route). The efficiency of the proposed technique is validated through a case study including...
The platform we're proposing will be the main actor of the upcoming paradigm shift from representative governance to self governance, the architecture, functionality and interface of the platform was modelled after the human anatomy. Human decision making efficiency is dependent upon the governance system of the deciding agents and the roles they play. Aligning the context in which a decision impacting...
Sexual harassment at workplace has been a criticalchallenge for women, especially in the service sector due to oddworking hours. Companies and Government on their part havetaken up measures to protect women employees but theproblem seems persistent. To address this, we have designed aregulatory solution based on operant conditioning. Operantconditioning argues that people's behaviors are primarilycontrolled...
In state-of-the-art Software Transactional Memory (STM) systems, threads carry out the execution of transactions as non-interruptible tasks. Hence, a thread can react to the injection of a higher priority transactional task and take care of its processing only at the end of the currently executed transaction. In this article we pursue a paradigm shift where the execution of an in-memory transaction...
We present an original concept for patch generation: we propose to do it directly in production. Our idea is to generate patches on-the-fly based on automated analysis of the failure context. By doing this in production, the repair process has complete access to the system state at the point of failure. We propose to perform live regression testing of the generated patches directly on the production...
Temporal Pooling (TP) is a recent technique for processing temporal events by forming declarative representations of the complete sequences. In this paper, we examine and extend the functionality of the existing TP algorithm from the Hierarchical Temporal Memory (HTM) framework and introduce the Self-Organising Temporal Pooling (SOTP) architecture. The SOTP draws together the Merge Self-Organising...
Nowadays, developing effective techniques able to deal with data coming from structured domains is becoming crucial. In this context kernel methods are the state-of-the-art tool widely adopted in real-world applications that involve learning on structured data. Contrarily, when one has to deal with unstructured domains, deep learning methods represent a competitive, or even better, choice. In this...
The new challenges in the smart city context are mainly related to the stimulation of the city users towards taking more sustainable behaviors, in mobility and energy. The state of the art in this case is mainly focused on classical smart city solution for informing the city users and or for engaging them with specific wired rules toward virtuous models. And not using flexible languages and predictive...
Episodic memory which can store and recall episodes has been modeled by various research. Those models focus on encoding and retrieving the same sequence of events of episodes. In this paper, we propose context preference-based deep adaptive resonance theory (CPD-ART). CPD-ART uses a new approach in encoding and retrieving a temporal sequence of events considering subjects, preference criteria such...
The development of Fog Computing technology is crucial to address the challenges to come with the mass adoption of Internet Of Things technology, where the generation of data tends to grow at an unprecedented pace. The technology brings computing power to the surrounds of devices, to offer local processing, filtering, storage and analysis of data and control over actuators. Orchestration is a requirement...
The abstraction tasks are challenging for multi-modal sequences as they require a deeper semantic understanding and a novel text generation for the data. Although the recurrent neural networks (RNN) can be used to model the context of the time-sequences, in most cases the long-term dependencies of multi-modal data make the back-propagation through time training of RNN tend to vanish in the time domain...
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