VIRTUOS - Virtualisation and Operating Systems
Recerca en optimització de sistemes operatius i tecnologies de virtualització, especialment tecnologies de virtualització lleugera com contenidors i unikernels. El grup de recerca està format per un equip interdisciplinar amb perfils complementaris que cobreixen un gran ventall de especialitzacions i amb àrees de interès aplicades a diversos entorns, com ara datacenters, cyber-physical systems i edge computing. Aquestes àrees d’interès són principalment optimització en la gestió de recursos hardware i software, tant per part del sistema operatiu com per part dels elements virtualitzats, tecnologies de privacitat i seguretat, metodologies de fiabilitat i resiliència i models matemàtics per caracteritzar i optimitzar parts del sistema.
Investigación en optimización de sistemas operativos y tecnologías de virtualización, especialmente tecnologías de virtualización ligera como contenedores y unikernels. El grupo de investigación está formado por un equipo interdisciplinar con perfiles complementarios que cubren un gran abanico de especializaciones y con áreas de interés aplicadas a diversos entornos, tales como datacenters, cyber-physical Systems y edge computing. Estas áreas de interés son principalmente optimización en la gestión de recursos hardware y software, tanto por parte del sistema operativo como por parte de los elementos virtualizados, tecnologías de privacidad y seguridad, metodologías de fiabilidad y resiliencia y modelos matemáticos para caracterizar y optimizar partes del sistema.
Research aimed at optimization of Operating Systems and virtualization technologies, especially lightweight virtualization technologies such as containers and unikernels. The research group comprises interdisciplinary members with complementary skills that meet a wide range of specializations and with areas of interest targeting different environments, like datacenters, cyber-physical systems and edge computing. These areas of interest are mainly optimization of hardware and software resource management, whether on the part of operating system or on the part of virtualized elements, privacy and security technologies, methodologies of reliability and resiliency and mathematic models to characterize and optimize parts of the system.
Research aimed at optimization of Operating Systems and virtualization technologies, especially lightweight virtualization technologies such as containers and unikernels. The research group comprises interdisciplinary members with complementary skills that meet a wide range of specializations and with areas of interest targeting different environments, like datacenters, cyber-physical systems and edge computing. These areas of interest are mainly optimization of hardware and software resource management, whether on the part of operating system or on the part of virtualized elements, privacy and security technologies, methodologies of reliability and resiliency and mathematic models to characterize and optimize parts of the system.
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Articles de revista [15]
Recent Submissions
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Epicentral region estimation using convolutional neural networks
(Springer Nature, 2022)
Conference report
Restricted access - publisher's policyRecent works have assessed the capability of deep neural networks of estimating the epicentral source region of a seismic event from a single-station three-channel signal. In all the cases, the geographical partitioning ... -
Malicious website detection through deep learning algorithms
(Springer Nature, 2022)
Conference report
Restricted access - publisher's policyTraditional methods that detect malicious websites, such as blacklists, do not update frequently, and they cannot detect new attackers. A system capable of detecting malicious activity using Deep Learning (DL) has been ... -
Deep learning detection of GPS spoofing
(Springer Nature, 2022)
Conference report
Restricted access - publisher's policyUnmanned aerial vehicles (UAVs) are widely deployed in air navigation, where numerous applications use them for safety-of-life and positioning, navigation, and timing tasks. Consequently, GPS spoofing attacks are more and ... -
Fast and accurate SER estimation for large combinational blocks in early stages of the design
(Institute of Electrical and Electronics Engineers (IEEE), 2021-07-01)
Article
Open AccessSoft Error Rate (SER) estimation is an important challenge for integrated circuits because of the increased vulnerability brought by technology scaling. This paper presents a methodology to estimate in early stages of the ... -
A survey of deep learning techniques for cybersecurity in mobile networks
(2021-06-07)
Article
Open AccessThe widespread use of mobile devices, as well as the increasing popularity of mobile services has raised serious cybersecurity challenges. In the last years, the number of cyberattacks has grown dramatically, as well as ... -
SRAM arrays with built-in parity computation for real-time error detection in cache tag arrays
(Institute of Electrical and Electronics Engineers (IEEE), 2021)
Conference report
Open AccessThis work proposes an SRAM array with built-in real-time error detection (RTD) capabilities. Each cell in the new RTD-SRAM array computes its part of the real-time parity of an SRAM array column on-the-fly. RTD based arrays ... -
Technological layer
(The Institution of Engineering and Technology, 2020-10)
Part of book or chapter of book
Restricted access - publisher's policyThis chapter describes the fundamental characteristics of Complementary Metal-Oxide-Semiconductor (CMOS) technology, and how it can be assessed for system reliability studies. After some definitions, the dominating ... -
Platform-agnostic steal-time measurement in a guest operating system
(2018-10)
Research report
Open AccessSteal time is a key performance metric for applications executed in a virtualized environment. Steal time measures the amount of time the processor is preempted by code outside the virtualized environment. This, in turn, ... -
2D error correction for F/F based arrays using in-situ Real-Time Error Detection (RTD)
(Institute of Electrical and Electronics Engineers (IEEE), 2020)
Conference lecture
Open AccessThis work proposes in-situ Real-Time Error Detection (RTD): embedding hardware in a memory array for detecting a fault in the array when it occurs, rather than when it is read. RTD breaks the serialization between data ... -
Deep neural networks for earthquake detection and source region estimation in north-central Venezuela
(2020-10-01)
Article
Open AccessReliable earthquake detection algorithms are necessary to properly analyze and catalog the continuously growing seismic records. We report the results of applying a deep convolutional neural network, called UPC‐UCV ... -
Random forest parameterization for earthquake catalog generation
(Springer, 2020)
Conference report
Open AccessAn earthquake is the vibration pattern of the Earth’s crust induced by the sliding of geological faults. They are usually recorded for later studies. However, strong earthquakes are rare, small-magnitude events may pass ... -
Privacy preserving deep learning framework in fog computing
(Springer, 2020)
Conference report
Open AccessNowadays, the widespread use of mobile devices has raised serious cybersecurity challenges. Mobile services and applications use deep learning (DL) models for the modelling, classification and recognition of complex data, ...
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