Browsing by Author "Berral García, Josep Lluís"
Now showing items 1-20 of 52
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A highly parameterizable framework for Conditional Restricted Boltzmann Machine based workloads accelerated with FPGAs and OpenCL
(Elsevier, 2020-03-01)
Article
Open AccessConditional Restricted Boltzmann Machine (CRBM) is a promising candidate for a multidimensional system modeling that can learn a probability distribution over a set of data. It is a specific type of an artificial neural ... -
A Quick View on Current Techniques and Machine Learning Algorithms for Big Data Analytics
(Institute of Electrical and Electronics Engineers (IEEE), 2016)
Conference report
Open AccessBig-data is an excellent source of knowledge and information from our systems and clients, but dealing with such amount of data requires automation, and this brings us to data mining and machine leaming techniques. In ... -
A resilient and distributed near real-time traffic forecasting application for Fog computing environments
(Elsevier, 2018-10)
Article
Open AccessIn this paper we propose an architecture for a city-wide traffic modeling and prediction service based on the Fog Computing paradigm. The work assumes an scenario in which a number of distributed antennas receive data ... -
A resilient and distributed near real-time traffic forecasting application for Fog computing environments
(Elsevier, 2018-10-01)
Article
Open AccessIn this paper we propose an architecture for a city-wide traffic modeling and prediction service based on the Fog Computing paradigm. The work assumes an scenario in which a number of distributed antennas receive data ... -
Adaptive distributed mechanism againts flooding network attacks based on machine learning
(ACM Press, NY, 2008)
Conference report
Restricted access - publisher's policyAdaptive techniques based on machine learning and data mining are gaining relevance in self-management and self- defense for networks and distributed systems. In this paper, we focus on early detection and stopping of ... -
Adaptive on-line software aging prediction based on machine learning
(IEEE Computer Society Publications, 2010)
Conference report
Open AccessThe growing complexity of software systems is resulting in an increasing number of software faults. According to the literature, software faults are becoming one of the main sources of unplanned system outages, and have ... -
Adaptive prediction models for data center resources utilization estimation
(2019-12)
Article
Open AccessAccurate estimation of data center resource utilization is a challenging task due to multi-tenant co-hosted applications having dynamic and time-varying workloads. Accurate estimation of future resources utilization helps ... -
Adaptive scheduling on power-aware managed data-centers using machine learning
(IEEE Computer Society Publications, 2011)
Conference report
Restricted access - publisher's policyEnergy-related costs have become one of the major economic factors in IT data-centers, and companies and the research community are currently working on new efficient power-aware resource management strategies, also known ... -
Adaptive scheduling on power-aware managed data-centers using machine learning
(2011)
Research report
Open AccessEnergy-related costs have become one of the major economic factors in IT data-centers, and companies and the research community are currently working on new efficient power-aware resource management strategies, also known ... -
Adaptive sliding windows for improved estimation of data center resource utilization
(Elsevier, 2020-03)
Article
Open AccessAccurate prediction of data center resource utilization is required for capacity planning, job scheduling, energy saving, workload placement, and load balancing to utilize the resources efficiently. However, accurately ... -
ALOJA-ML: a framework for automating characterization and knowledge discovery in Hadoop deployments
(Association for Computing Machinery (ACM), 2015)
Conference report
Open AccessThis article presents ALOJA-Machine Learning (ALOJA-ML) an extension to the ALOJA project that uses machine learning techniques to interpret Hadoop benchmark performance data and performance tuning; here we detail the ... -
ALOJA: A benchmarking and predictive platform for big data performance analysis
(Springer, 2016)
Conference report
Open AccessThe main goals of the ALOJA research project from BSC-MSR, are to explore and automate the characterization of cost-effectivenessof Big Data deployments. The development of the project over its first year, has resulted in ... -
ALOJA: A framework for benchmarking and predictive analytics in Hadoop deployments
(Institute of Electrical and Electronics Engineers (IEEE), 2015-10)
Article
Open AccessThis article presents the ALOJA project and its analytics tools, which leverages machine learning to interpret Big Data benchmark performance data and tuning. ALOJA is part of a long-term collaboration between BSC and ... -
An integer linear programming representation for data-center power-aware management
(2010-11-12)
Research report
Open AccessThis work exposes how to represent a grid data-center based scheduling problem, taking the advantages of the virtualization and consolidation techniques, as a linear integer programming problem including all three mentioned ... -
Automatic distributed deep learning using resource-constrained edge devices
(Institute of Electrical and Electronics Engineers (IEEE), 2022-08-15)
Article
Open AccessProcessing data generated at high volume and speed from the Internet of Things, smart cities, domotic, intelligent surveillance, and e-healthcare systems require efficient data processing and analytics services at the Edge ... -
Automatic generation of workload profiles using unsupervised learning pipelines
(2017-12-27)
Article
Open AccessThe complexity of resource usage and power consumption on cloud-based applications makes the understanding of application behavior through expert examination difficult. The difficulty increases when applications are seen ... -
Building green cloud services at low cost
(Institute of Electrical and Electronics Engineers (IEEE), 2014)
Conference lecture
Open AccessInterest in powering datacenters at least partially using on-site renewable sources, e.g. solar or wind, has been growing. In fact, researchers have studied distributed services comprising networks of such “green” datacenters, ... -
Burst-aware predictive autoscaling for containerized microservices
(2022-05-01)
Article
Open AccessAutoscaling methods are used for cloud-hosted applications to dynamically scale the allocated resources for guaranteeing Quality-of-Service (QoS). The public-facing application serves dynamic workloads, which contain bursts ... -
Clustering and graph mining techniques for classification of complex structural variations in cancer genomes
(Nature, 2022-02-28)
Article
Open AccessFor many years, a major question in cancer genomics has been the identification of those variations that can have a functional role in cancer, and distinguish from the majority of genomic changes that have no functional ... -
Constant-time sliding window framework with reduced memory footprint and efficient bulk evictions
(2019-03)
Article
Open AccessThe fast evolution of data analytics platforms has resulted in an increasing demand for real-time data stream processing. From Internet of Things applications to the monitoring of telemetry generated in large data centers, ...
