Search results for "Tribute"

showing 10 items of 1455 documents

Low-Power Wide-Area Networks for Sustainable IoT

2019

Low-power wide-area (LPWA) networks are attracting extensive attention because of their abilities to offer low-cost and massive connectivity to Internet of Things (IoT) devices distributed over wide geographical areas. This article provides a brief overview on the existing LPWA technologies and useful insights to aid the large-scale deployment of LPWA networks. Particularly, we first review the currently competing candidates of LPWA networks, such as narrowband IoT (NB-IoT) and long range (LoRa), in terms of technical fundamentals and large-scale deployment potential. Then we present two implementation examples on LPWA networks. By analyzing the field-test results, we identify several chall…

FOS: Computer and information sciencesComputer scienceComputer Science - Information Theory0805 Distributed Computing02 engineering and technologylaw.inventionComputer Science - Networking and Internet ArchitectureBluetoothGSMlaw1005 Communications Technologies0202 electrical engineering electronic engineering information engineeringBandwidth (computing)Resource managementElectrical and Electronic EngineeringNetworking and Internet Architecture (cs.NI)business.industryInformation Theory (cs.IT)020206 networking & telecommunicationsComputer Science ApplicationsPower (physics)0906 Electrical and Electronic EngineeringWide areaSoftware deploymentNetworking & TelecommunicationsTelecommunicationsbusinessInternet of Things
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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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Efficient and accurate monitoring of the depth information in a Wireless Multimedia Sensor Network based surveillance

2017

International audience; Abstract—Wireless Multimedia Sensor Network (WMSN) is a promising technology capturing rich multimedia data like audio and video, which can be useful to monitor an environment under surveillance. However, many scenarios in real time monitoring requires 3D depth information. In this research work, we propose to use the disparity map that is computed from two or multiple images, in order to monitor the depth information in an object or event under surveillance using WMSN. Our system is based on distributed wireless sensors allowing us to notably reduce the computational time needed for 3D depth reconstruction, thus permitting the success of real time solutions. Each pa…

FOS: Computer and information sciencesComputer scienceComputer Vision and Pattern Recognition (cs.CV)Real-time computingComputer Science - Computer Vision and Pattern Recognition[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]02 engineering and technologyImage (mathematics)[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]0202 electrical engineering electronic engineering information engineeringWirelessWireless multimedia sensor networksEvent (computing)business.industryNode (networking)Bandwidth (signal processing)020206 networking & telecommunicationsObject (computer science)[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationStereopsis[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]020201 artificial intelligence & image processing[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]business2017 Sensors Networks Smart and Emerging Technologies (SENSET)
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Capture Aware Sequential Waterfilling for LoraWAN Adaptive Data Rate

2020

LoRaWAN (Long Range Wide Area Network) is emerging as an attractive network infrastructure for ultra low power Internet of Things devices. Even if the technology itself is quite mature and specified, the currently deployed wireless resource allocation strategies are still coarse and based on rough heuristics. This paper proposes an innovative "sequential waterfilling" strategy for assigning Spreading Factors (SF) to End-Devices (ED). Our design relies on three complementary approaches: i) equalize the Time-on-Air of the packets transmitted by the system's EDs in each spreading factor's group; ii) balance the spreading factors across multiple access gateways, and iii) keep into account the c…

FOS: Computer and information sciencesComputer scienceDistributed computingInternet of ThingsWireless communicationresource allocationServers02 engineering and technologyNetwork topologyspreading factorsinter-SF interferenceComputer Science - Networking and Internet Architecturechannel captureBandwidthServerLPWAN0202 electrical engineering electronic engineering information engineeringWirelessComputer architectureElectrical and Electronic Engineeringinternet of t6hingsNetworking and Internet Architecture (cs.NI)Network packetbusiness.industryApplied MathematicsResource managementinternet of t6hings; LoRaWAN; spreading factors; resource allocation; adaptive data rate; channel capture; inter-SF interference020206 networking & telecommunicationsComputer Science ApplicationsLoRaWANadaptive data rateWide area networkScalabilityHeuristicsbusinessInterferenceUplinkCommunication channel
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Impact of LTE’s Periodic Interference on Heterogeneous Wi-Fi Transmissions

2018

The problem of Wi-Fi and LTE coexistence has been significantly debated in the last years, with the emergence of LTE extensions enabling the utilization of unlicensed spectrum for carrier aggregation. Rather than focusing on the problem of resource sharing between the two technologies, in this paper, we study the effects of LTE's structured transmissions on the Wi-Fi random access protocol. We show how the scheduling of periodic LTE transmissions modifies the behavior of 802.11's distributed coordination function (DCF), leading to a degradation of Wi-Fi performance, both in terms of channel utilization efficiency and in terms of channel access fairness. We also discuss the applicability and…

FOS: Computer and information sciencesComputer scienceThroughput02 engineering and technologyDistributed coordination functionSpectrum managementAnalytical modelScheduling (computing)Computer Science - Networking and Internet ArchitectureC.2.0C.2.50202 electrical engineering electronic engineering information engineeringLong Term EvolutionWireless fidelityElectrical and Electronic EngineeringProbabilitySensorNetworking and Internet Architecture (cs.NI)business.industrySettore ING-INF/03 - TelecomunicazioniComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS020206 networking & telecommunicationsComputer Science Applications1707 Computer Vision and Pattern RecognitionThroughput91A06 91A10 91A80Computer Science ApplicationsShared resourceModeling and SimulationbusinessC.2.0; C.2.5InterferenceRandom accessComputer networkCommunication channel
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Multi-scale analysis of the European airspace using network community detection

2014

We show that the European airspace can be represented as a multi-scale traffic network whose nodes are airports, sectors, or navigation points and links are defined and weighted according to the traffic of flights between the nodes. By using a unique database of the air traffic in the European airspace, we investigate the architecture of these networks with a special emphasis on their community structure. We propose that unsupervised network community detection algorithms can be used to monitor the current use of the airspaces and improve it by guiding the design of new ones. Specifically, we compare the performance of three community detection algorithms, also by using a null model which t…

FOS: Computer and information sciencesDatabases FactualDistributed computingSocial SciencesPoison controllcsh:MedicineSociologycommunity detectionData Mininglcsh:SciencePhysicsMultidisciplinaryMathematical modelApplied MathematicsPhysicsCommunity structureComputer Science - Social and Information NetworksAir traffic controlAir TravelSocial NetworksPhysical SciencesInterdisciplinary PhysicsSocial SystemsEngineering and TechnologyFree flightInformation TechnologyNetwork AnalysisAlgorithmsResearch ArticlePhysics - Physics and SocietyComputer and Information SciencesControl (management)FOS: Physical sciencesComputerApplications_COMPUTERSINOTHERSYSTEMSPhysics and Society (physics.soc-ph)Statistical MechanicsDatabasescomplex networkHumansArchitectureNetworks network communities socio-technical system complex systems Air Traffic ManagementSocial and Information Networks (cs.SI)Null modellcsh:RModels TheoreticalSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Computational SociologySignal ProcessingAir trafficlcsh:QMathematics
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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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Online shortest paths with confidence intervals for routing in a time varying random network

2018

International audience; The increase in the world's population and rising standards of living is leading to an ever-increasing number of vehicles on the roads, and with it ever-increasing difficulties in traffic management. This traffic management in transport networks can be clearly optimized by using information and communication technologies referred as Intelligent Transport Systems (ITS). This management problem is usually reformulated as finding the shortest path in a time varying random graph. In this article, an online shortest path computation using stochastic gradient descent is proposed. This routing algorithm for ITS traffic management is based on the online Frank-Wolfe approach.…

FOS: Computer and information sciencesMathematical optimizationComputer sciencePopulation02 engineering and technology[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE][INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[SPI]Engineering Sciences [physics][INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]0502 economics and business11. SustainabilityComputer Science - Data Structures and Algorithms0202 electrical engineering electronic engineering information engineeringFOS: MathematicsData Structures and Algorithms (cs.DS)educationIntelligent transportation systemMathematics - Optimization and ControlRandom graph050210 logistics & transportationeducation.field_of_studyStochastic process[SPI.PLASMA]Engineering Sciences [physics]/Plasmas05 social sciencesApproximation algorithm[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationStochastic gradient descentOptimization and Control (math.OC)[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Shortest path problem020201 artificial intelligence & image processing[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Routing (electronic design automation)[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]
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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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