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A FIWARE-Based Component for Data Analysis in Smart Mobility Context

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A FIWARE-Based Component for Data Analysis in Smart Mobility...

IEEE First Summer School on Smart Cities (S3C)

作者： Rosangela de Fátima Pereira Marquesone Tereza Cristina Melo de Brito Carvalho Lucas Batista Guimarães Eduardo Mario Dias Laboratory of Computer Networks and Architecture - LARC Polytechnic School University of São Paulo São Paulo Brazil Department of Energy Engineering and Automation Polytechnic School University of São Paulo São Paulo Brazil

Smart mobility is an emerging concept characterized by the use of disruptive technologies, such as cloud computing, Big Data and artificial intelligence. In this paper we propose a FIWARE-based component focus on improving the data analysis process, from data generated in services and applications existing in the smart mobility context. Our proposal aims to provide features that allows the development of solutions from the industry 4.0 concept and smart cities. Firstly, we briefly contextualize these terms, then we describe the characteristics and architectural design of our FIWARE component, highlighting how it can improve the support to smart services and applications. We also present real application scenarios where this component can be applied, specially considering the Brazilian cities.

关键词： Data analysis Big Data Internet Companies Smart cities

Local energy micro-storage systems in smart communities with active, reactive and harmonic control

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Local energy micro-storage systems in smart communities with...

International Conference on Environment and Electrical Engineering (EEEIC)

作者： María-Isabel Milanés-Montero Eva González- Romera Fermín Barrero-González Enrique Romero-Cadaval Antonio Moreno-Munoz Universidad de Extremadura Caceres Extremadura ES Electrical Electronic and Automation Engineering Dept. University of Extremadura Badajoz Spain Computer Architecture Electronics and Electronic Technology Department Universidad de Córdoba Córdoba Spain

ISBN: (纸本)9781509023219

This paper aims to provide control strategies for distributed micro-storage energy systems at the residential level to contribute to smart grid goals. The operation of local Energy Storage Systems (ESS) at homes in a Smart Community with distributed generation based of renewable energies is analyzed by simulation. Each individual home receive the active and reactive power set-points from the Smart Community Energy Management System (SCEMS), acting as an aggregator of resources in the community according to the expected demand and production. Besides, in case the ESS has got available capacity, once the SCEMS requirements are satisfied, it is used to inject the harmonic current components demanded by the household circuitry. It allows a local improvement in the power quality of the demanded current, and so contributes to the global power quality consumption of the community. Simulation results showing the operation of the local ESS are presented to validate the proposed control strategies.

关键词： Harmonic analysis Reactive power Simulation Power quality Batteries Power system harmonics

A parallel evolutionary algorithm to optimize dynamic memory managers in embedded systems

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arXiv 2024年

作者： Risco-Martín, José L. Atienza, David Colmenar, J. Manuel Garnica, Oscar Department of Computer Architecture and Automation Universidad Complutense de Madrid Madrid28040 Spain Lausanne1015 Switzerland C. E. S. Felipe II Universidad Complutense de Madrid Aranjuez28300 Spain

For the last thirty years, several Dynamic Memory Managers (DMMs) have been proposed. Such DMMs include first fit, best fit, segregated fit and buddy systems. Since the performance, memory usage and energy consumption of each DMM differs, software engineers often face difficult choices in selecting the most suitable approach for their applications. This issue has special impact in the field of portable consumer embedded systems, that must execute a limited amount of multimedia applications (e.g., 3D games, video players and signal processing software, etc.), demanding high performance and extensive memory usage at a low energy consumption. Recently, we have developed a novel methodology based on genetic programming to automatically design custom DMMs, optimizing performance, memory usage and energy consumption. However, although this process is automatic and faster than state-of-the-art optimizations, it demands intensive computation, resulting in a time consuming process. Thus, parallel processing can be very useful to enable to explore more solutions spending the same time, as well as to implement new algorithms. In this paper we present a novel parallel evolutionary algorithm for DMMs optimization in embedded systems, based on the Discrete Event Specification (DEVS) formalism over a Service Oriented architecture (SOA) framework. Parallelism significantly improves the performance of the sequential exploration algorithm. On the one hand, when the number of generations are the same in both approaches, our parallel optimization framework is able to reach a speed-up of 86.40× when compared with other state-of-the-art approaches. On the other, it improves the global quality (i.e., level of performance, low memory usage and low energy consumption) of the final DMM obtained in a 36.36% with respect to two well-known general-purpose DMMs and two state-of-the-art optimization methodologies. © 2024, CC BY-SA.

关键词： Energy utilization

Simulation of High-Performance Memory Allocators

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arXiv 2024年

作者： Risco-Martín, José L. Colmenar, J. Manuel Atienza, David Hidalgo, J. Ignacio Department of Computer Architecture and Automation Universidad Complutense de Madrid Madrid28040 Spain C. E. S. Felipe II Universidad Complutense de Madrid Aranjuez28300 Spain Lausanne1015 Switzerland

For the last thirty years, a large variety of memory allocators have been proposed. Since performance, memory usage and energy consumption of each memory allocator differs, software engineers often face difficult choices in selecting the most suitable approach for their applications. To this end, custom allocators are developed from scratch, which is a difficult and error-prone process. This issue has special impact in the field of portable consumer embedded systems, that must execute a limited amount of multimedia applications, demanding high performance and extensive memory usage at a low energy consumption. This paper presents a flexible and efficient simulator to study Dynamic Memory Managers (DMMs), a composition of one or more memory allocators. This novel approach allows programmers to simulate custom and general DMMs, which can be composed without incurring any additional runtime overhead or additional programming cost. We show that this infrastructure simplifies DMM construction, mainly because the target application does not need to be compiled every time a new DMM must be evaluated and because we propose a structured method to search and build DMMs in an object-oriented fashion. Within a search procedure, the system designer can choose the "best" allocator by simulation for a particular target application and embedded system. In our evaluation, we show that our scheme delivers better performance, less memory usage and less energy consumption than single memory allocators. © 2024, CC BY-SA.

关键词： Embedded systems

Job Scheduling with License Reservation: A Semantic Approach

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Job Scheduling with License Reservation: A Semantic Approach

Euromicro Conference on Parallel, Distributed and Network-Based Processing

作者： Jorge Ejarque Andras Micsik Raul Sirvent Peter Pallinger Laszlo Kovacs Rosa M. Badia Computer Architecture Department Universitat Politecnica de Catalunya Barcelona Spain Grid Computing and Clusters Group Barcelona Supercomputing Center Barcelona Spain Distributed Systems Department-Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Artificial Intelligence Research Institute Spanish National Research Council Barcelona Spain

The license management is one of the main concerns when Independent Software Vendors (ISV) try to distribute their software in computing platforms such as Clouds. They want to be sure that customers use their software according to their license terms. The work presented in this paper tries to solve part of this problem extending a semantic resource allocation approach for supporting the scheduling of job taking into account software licenses. This approach defines the licenses as another type of computational resource which is available in the system and must be allocated to the different jobs requested by the users. License terms are modeled as resource properties, which describe the license constraints. A resource ontology has been extended in order to model the relations between customers, providers, jobs, resources and licenses in detail and make them machine processable. The license scheduling has been introduced in a semantic resource allocation process by providing a set of rules, which evaluate the semantic license terms during the job scheduling.

关键词： Licenses Software Semantics Resource management Ontologies Processor scheduling Law

Factoring integers via Schnorr’s algorithm assisted with VQE

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arXiv 2024年

作者： Sánchez Cano, Luis Carrascal de las Heras, Ginés Botella Juan, Guillermo del Barrio García, Alberto Iberdrola S.A. Madrid28033 Spain IT Systems and Computation Department Complutense University of Madrid Madrid28040 Spain IBM Quantum IBM Consulting España Madrid28830 Spain Computer Architecture and Automation Department Complutense University of Madrid Madrid28040 Spain

Current asymmetric cryptography is based on the principle that while classical computers can efficiently multiply large integers, the inverse operation, factorization, is significantly more complex. For sufficiently large integers, this factorization process can take in classical computers hundreds or even thousands of years to complete. However, there exist some quantum algorithms that might be able to factor integers theoretically - the theory works properly, but the hardware requirements are far away from what we can build nowadays - and, for instance, Yan, B. et al. ([14]) claim to have constructed a hybrid algorithm which could be able even to challenge RSA-2048 in the near future. This work analyses this article and replicates the experiments they carried out, but with a different quantum method (VQE), being able to factor the number 1961. Copyright © 2024, The Authors. All rights reserved.

关键词： Encryption algorithms

Group-wise sparse representation of brain states reveal network abnormalities in mild traumatic brain injury

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Group-wise sparse representation of brain states reveal netw...

IEEE International Symposium on Biomedical Imaging

作者： Jinglei Lv Armin Iraji Hanbo Chen Fangfei Ge Lei Guo Xin Zhang Zhifeng Kou Tianming Liu School of Automation Northwestern Polytechnical University Xi'an China Biomedical Engineering and Radiology Wayne State University Detroit Michigan Cortical Architecture Imaging and Discovery Lab Department of Computer Science and Bioimaging Research Center The University of Georgia Athens GA

ISBN: (纸本)9781479923519

Mild traumatic brain injury (mTBI) is a leading public health care burden. Recent research has shown that the functional impairment in mTBI patients could be captured by resting state fMRI (rsfMRI) at network level. Moreover exploring brain response to mTBI over time at large scale network level can help physicians better diagnose brain injury and order appropriate rehabilitation plan. Therefore, there is a need for methodological innovation that could assess brain impairment in rsfMRI data and further define biomarkers for network changes. In this paper, we propose a novel group-wise sparse representation of brain states (GSRBS) approach, based on rsfMRI data, to explore the effect of mTBI on functional networks across different groups and longitudinal stages. Specifically, a dictionary of brain networks is learned from the volumes of rsfMRI data, and at each time point these networks are linearly and sparsely combined to realize a brain state. Our results showed that group-wise statistical difference on the network composition of brain states could be found between healthy controls and mTBI patients at two different temporal stages.

关键词： Dictionaries Encoding Brain injuries Learning systems Training Biomedical imaging

POSTER: Performance evaluation of a signal extraction algorithm for the Cherenkov Telescope Array's Real Time Analysis pipeline

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POSTER: Performance evaluation of a signal extraction algori...

IEEE International Conference on Cluster Computing

作者： Juan José Rodríguez-Vázquez José Luis Vázquez-Poletti Carlos Delgado Andrea Bulgarelli Miguel Cárdenas-Montes Department of Fundamental Research CIEMAT Madrid Spain Dept. of Computer Architecture and Automation Complutense University of Madrid Madrid Spain Istituto di Astrofisica Spaziale e Fisica Cosmica Bologna /Istituto Nazionale di Astrofisica Bologna Italy

In this paper, several versions of a signal extraction algorithm, pertaining to the entry stage of the Cherenkov Telescope Array's Real Time Analysis pipeline, were implemented and optimised using SSE2, POSIX threads and CUDA. Results of this proof of concept let us gain an insight into the suitability of each platform, and the performance each one can deliver, to carry out this particular task.

关键词： Graphics processing units Telescopes Real-time systems Pipelines Random access memory Central Processing Unit Throughput

Sustainable Edge Computing: Challenges and Future Directions

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arXiv 2023年

作者： Arroba, Patricia Buyya, Rajkumar Cárdenas, Román Risco-Martín, José L. Moya, José M. CCS–Center for Computational Simulation ETSI Telecomunicación Universidad Politécnica de Madrid Spain Lab School of Computing and Information Systems The University of Melbourne Australia Department of Computer Architecture and Automation Universidad Complutense de Madrid Spain

An increasing amount of data is being injected into the network from IoT (Internet of Things) applications. Many of these applications, developed to improve society's quality of life, are latency-critical and inject large amounts of data into the network. These requirements of IoT applications trigger the emergence of Edge computing paradigm. Currently, data centers are responsible for a global energy use between 2% and 3%. However, this trend is difficult to maintain, as bringing computing infrastructures closer to the edge of the network comes with its own set of challenges for energy efficiency. In this paper, we propose our approach for the sustainability of future computing infrastructures to provide (i) an energy-efficient and economically viable deployment, (ii) a fault-tolerant automated operation, and (iii) a collaborative resource management to improve resource efficiency. We identify the main limitations of applying Cloud-based approaches close to the data sources and present the research challenges to Edge sustainability arising from these constraints. We propose two-phase immersion cooling, formal modeling, machine learning, and energy-centric federated management as Edge-enabling technologies. We present our early results towards the sustainability of an Edge infrastructure to demonstrate the benefits of our approach for future computing environments and deployments. © 2023, CC BY.

关键词： Internet of things