Search results for "Computer Science - Distributed"

showing 10 items of 22 documents

Investigating Low Level Protocols for Wireless Body Sensor Networks

2016

The rapid development of medical sensors has increased the interest in Wireless Body Area Network (WBAN) applications where physiological data from the human body and its environment is gathered, monitored, and analyzed to take the proper measures. In WBANs, it is essential to design MAC protocols that ensure adequate Quality of Service (QoS) such as low delay and high scalability. This paper investigates Medium Access Control (MAC) protocols used in WBAN, and compares their performance in a high traffic environment. Such scenario can be induced in case of emergency for example, where physiological data collected from all sensors on human body should be sent simultaneously to take appropria…

FOS: Computer and information sciencesComputer scienceComputer Science - Information TheoryTime division multiple accessAccess control[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]02 engineering and technology[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]Body area network0202 electrical engineering electronic engineering information engineeringWirelessProtocol (science)business.industryInformation Theory (cs.IT)Quality of service020208 electrical & electronic engineeringComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS020206 networking & telecommunications[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationComputer Science - Distributed Parallel and Cluster Computing[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Scalability[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Distributed Parallel and Cluster Computing (cs.DC)[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]businessWireless sensor networkComputer network
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Unified System for Processing Real and Simulated Data in the ATLAS Experiment

2015

The physics goals of the next Large Hadron Collider run include high precision tests of the Standard Model and searches for new physics. These goals require detailed comparison of data with computational models simulating the expected data behavior. To highlight the role which modeling and simulation plays in future scientific discovery, we report on use cases and experience with a unified system built to process both real and simulated data of growing volume and variety.

FOS: Computer and information sciencesJ.2Physics - Instrumentation and Detectors68T42FOS: Physical sciencesInstrumentation and Detectors (physics.ins-det)High Energy Physics - ExperimentComputing and ComputersC.1.4H.3.4High Energy Physics - Experiment (hep-ex)Computer Science - Distributed Parallel and Cluster ComputingI.6.7Distributed Parallel and Cluster Computing (cs.DC)C.1.4; H.3.4; I.6.7; J.2
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The IceProd framework: distributed data processing for the IceCube neutrino observatory

2015

IceCube is a one-gigaton instrument located at the geographic South Pole, designed to detect cosmic neutrinos, identify the particle nature of dark matter, and study high-energy neutrinos themselves. Simulation of the IceCube detector and processing of data require a significant amount of computational resources. This paper presents the first detailed description of IceProd, a lightweight distributed management system designed to meet these requirements. It is driven by a central database in order to manage mass production of simulations and analysis of data produced by the IceCube detector. IceProd runs as a separate layer on top of other middleware and can take advantage of a variety of c…

FOS: Computer and information sciencesMonitoringComputer scienceComputer Networks and CommunicationsDistributed computingData managementReal-time computingDistributed managementcomputer.software_genre01 natural sciencesData managementIceCube Neutrino ObservatoryTheoretical Computer ScienceIceCubeArtificial Intelligence0103 physical sciences010306 general physicsData processingData management; Distributed computing; Grid computing; Monitoring010308 nuclear & particles physicsbusiness.industryDistributed computingGrid computingComputer Science - Distributed Parallel and Cluster ComputingHardware and ArchitectureMiddleware (distributed applications)MiddlewareGrid computingParticleDistributed Parallel and Cluster Computing (cs.DC)Neutrinoddc:004businesscomputerSoftware
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Real-time computation of parameter fitting and image reconstruction using graphical processing units

2016

Abstract In recent years graphical processing units (GPUs) have become a powerful tool in scientific computing. Their potential to speed up highly parallel applications brings the power of high performance computing to a wider range of users. However, programming these devices and integrating their use in existing applications is still a challenging task. In this paper we examined the potential of GPUs for two different applications. The first application, created at Paul Scherrer Institut (PSI), is used for parameter fitting during data analysis of μ SR (muon spin rotation, relaxation and resonance) experiments. The second application, developed at ETH, is used for PET (Positron Emission T…

FOS: Computer and information sciencesMulti-core processorSpeedup010308 nuclear & particles physicsComputer scienceComputationFOS: Physical sciencesGeneral Physics and AstronomyIterative reconstructionComputational Physics (physics.comp-ph)Supercomputer01 natural sciences030218 nuclear medicine & medical imagingComputational science03 medical and health sciencesRange (mathematics)CUDA0302 clinical medicineComputer Science - Distributed Parallel and Cluster ComputingHardware and Architecture0103 physical sciencesSingle-coreDistributed Parallel and Cluster Computing (cs.DC)Physics - Computational PhysicsComputer Physics Communications
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P2P-PL: A pattern language to design efficient and robust peer-to-peer systems

2017

To design peer-to-peer (P2P) software systems is a challenging task, because of their highly decentralized nature, which may cause unexpected emergent global behaviors. The last fifteen years have seen many P2P applications to come out and win favor with millions of users. From success histories of applications like BitTorrent, Skype, MyP2P we have learnt a number of useful design patterns. Thus, in this article we present a P2P pattern language (shortly, P2P-PL) which encompasses all the aspects that a fully effective and efficient P2P software system should provide, namely consistency of stored data, redundancy, load balancing, coping with asymmetric bandwidth, decentralized security. The…

FOS: Computer and information sciencesPattern languageComputer Networks and CommunicationsComputer sciencebusiness.industryDistributed computing020206 networking & telecommunications02 engineering and technologycomputer.file_formatPeer-to-peerLoad balancing (computing)computer.software_genreSoftwareComputer Science - Distributed Parallel and Cluster ComputingRobustness (computer science)Software design patternC.2.40202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingDistributed Parallel and Cluster Computing (cs.DC)Software systembusinesscomputerBitTorrentSoftwarePeer-to-Peer Networking and Applications
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WarpCore: A Library for fast Hash Tables on GPUs

2020

Hash tables are ubiquitous. Properties such as an amortized constant time complexity for insertion and querying as well as a compact memory layout make them versatile associative data structures with manifold applications. The rapidly growing amount of data emerging in many fields motivated the need for accelerated hash tables designed for modern parallel architectures. In this work, we exploit the fast memory interface of modern GPUs together with a parallel hashing scheme tailored to improve global memory access patterns, to design WarpCore -- a versatile library of hash table data structures. Unique device-sided operations allow for building high performance data processing pipelines ent…

FOS: Computer and information sciencesScheme (programming language)Amortized analysisComputer scienceHash functionParallel computingData structureHash tableCUDAComputer Science - Distributed Parallel and Cluster ComputingServerDistributed Parallel and Cluster Computing (cs.DC)Throughput (business)computercomputer.programming_language2020 IEEE 27th International Conference on High Performance Computing, Data, and Analytics (HiPC)
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Blockchain-Based Proof of Location

2016

Location-Based Services (LBSs) build upon geographic information to provide users with location-dependent functionalities. In such a context, it is particularly important that geographic locations claimed by users are trustworthy. Centralized verification approaches proposed in the last few years are not satisfactory, as they entail a high risk to the privacy of users. In this paper, we present and evaluate a novel decentralized, infrastructure-independent proof-of-location scheme based on blockchain technology. Our scheme guarantees both location trustworthiness and user privacy preservation.

FOS: Computer and information sciencesScheme (programming language)Computer Science - Cryptography and SecurityBlockchainbusiness.industryComputer science020206 networking & telecommunicationsCryptographyContext (language use)02 engineering and technologyComputer securitycomputer.software_genreUser privacyTrustworthinessComputer Science - Distributed Parallel and Cluster Computing020204 information systemsServerC.2.40202 electrical engineering electronic engineering information engineeringPeer to peer computingDistributed Parallel and Cluster Computing (cs.DC)businessCryptography and Security (cs.CR)computercomputer.programming_language2018 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)
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Alignment-free Genomic Analysis via a Big Data Spark Platform

2021

Abstract Motivation Alignment-free distance and similarity functions (AF functions, for short) are a well-established alternative to pairwise and multiple sequence alignments for many genomic, metagenomic and epigenomic tasks. Due to data-intensive applications, the computation of AF functions is a Big Data problem, with the recent literature indicating that the development of fast and scalable algorithms computing AF functions is a high-priority task. Somewhat surprisingly, despite the increasing popularity of Big Data technologies in computational biology, the development of a Big Data platform for those tasks has not been pursued, possibly due to its complexity. Results We fill this impo…

FOS: Computer and information sciencesStatistics and Probabilitysequence analysisComputer science0206 medical engineeringBig data02 engineering and technologyMachine learningcomputer.software_genreBiochemistry03 medical and health sciencesSpark (mathematics)MapReduceMolecular Biology030304 developmental biology0303 health sciencesSettore INF/01 - Informaticabusiness.industryBioinformatics High Performance Computing Compressed Data StructuresMapReduce; hadoop; sequence analysisComputer Science ApplicationsComputational MathematicsTask (computing)Computer Science - Distributed Parallel and Cluster ComputingComputational Theory and MathematicsDistributed Parallel and Cluster Computing (cs.DC)Artificial intelligencehadoopbusinesscomputer020602 bioinformaticsBioinformatics
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Dirac equation as a quantum walk over the honeycomb and triangular lattices

2018

A discrete-time Quantum Walk (QW) is essentially an operator driving the evolution of a single particle on the lattice, through local unitaries. Some QWs admit a continuum limit, leading to well-known physics partial differential equations, such as the Dirac equation. We show that these simulation results need not rely on the grid: the Dirac equation in $(2+1)$--dimensions can also be simulated, through local unitaries, on the honeycomb or the triangular lattice. The former is of interest in the study of graphene-like materials. The latter, we argue, opens the door for a generalization of the Dirac equation to arbitrary discrete surfaces.

FOS: Computer and information sciences[ INFO ] Computer Science [cs]Differential equationFOS: Physical sciencestriangulation01 natural sciences010305 fluids & plasmassymbols.namesakeHigh Energy Physics - Lattice[PHYS.QPHY]Physics [physics]/Quantum Physics [quant-ph]Lattice (order)Mesoscale and Nanoscale Physics (cond-mat.mes-hall)0103 physical sciences[ PHYS.PHYS.PHYS-GEN-PH ] Physics [physics]/Physics [physics]/General Physics [physics.gen-ph]unitaritysurface[INFO]Computer Science [cs]Quantum walkHexagonal latticeDirac equationcontinuum limit010306 general physicsQuantumComputingMilieux_MISCELLANEOUSlatticeMathematical physicsPhysicsQuantum PhysicsPartial differential equationCondensed Matter - Mesoscale and Nanoscale PhysicsUnitarity[PHYS.HLAT]Physics [physics]/High Energy Physics - Lattice [hep-lat]High Energy Physics - Lattice (hep-lat)[ PHYS.HLAT ] Physics [physics]/High Energy Physics - Lattice [hep-lat]differential equations[PHYS.PHYS.PHYS-GEN-PH]Physics [physics]/Physics [physics]/General Physics [physics.gen-ph]Computer Science - Distributed Parallel and Cluster ComputingDirac equationsymbolsDistributed Parallel and Cluster Computing (cs.DC)Quantum Physics (quant-ph)Physical Review A
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MetaCache-GPU: Ultra-Fast Metagenomic Classification

2021

The cost of DNA sequencing has dropped exponentially over the past decade, making genomic data accessible to a growing number of scientists. In bioinformatics, localization of short DNA sequences (reads) within large genomic sequences is commonly facilitated by constructing index data structures which allow for efficient querying of substrings. Recent metagenomic classification pipelines annotate reads with taxonomic labels by analyzing their $k$-mer histograms with respect to a reference genome database. CPU-based index construction is often performed in a preprocessing phase due to the relatively high cost of building irregular data structures such as hash maps. However, the rapidly growi…

Genomics (q-bio.GN)FOS: Computer and information sciencesSource codeComputer sciencemedia_common.quotation_subjectHash functionContext (language use)MinHashcomputer.software_genreData structureHash tableComputer Science - Distributed Parallel and Cluster ComputingFOS: Biological sciencesPreprocessorQuantitative Biology - GenomicsDistributed Parallel and Cluster Computing (cs.DC)Data miningcomputermedia_commonReference genome50th International Conference on Parallel Processing
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