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检索条件"任意字段=IEEE International Conference on Distributed Computing in Sensor Systems"

共 30780 条记录，以下是4531-4540 订阅

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JADD-GAN: A Joint Attention Generative Adversarial Data Fusion Network for Object Detection and Tracking

JADD-GAN: A Joint Attention Generative Adversarial Data Fusi...

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ieee international conference on High Performance computing and Communications (HPCC)

作者： Guoxia Xu Hao Wang Meng Zhao Hu Zhu Department of Computer Science Norwegian University of Science and Technology Gjøvik Norway School of Computer Science and Engineering Tianjin University of Technology Tianjin China School of Communications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China

Image fusion is the fusion of images captured by different sensors to generate a single image with enhanced information, and fusion technology, as one of the important branches in the field of information fusion, mainly realizes the processing of multi-source image information. However, many commonly used fusion methods usually ignore the visual naturalness and information fidelity of the fused images and lack emphasis on the salient information, which makes the fused images unsuitable for human visual perception. To address these shortcomings of existing methods, in this paper, we propose the Joint Attention and Dual Discriminator Generative Adversarial Data Fusion Network JADD-GAN. In the generator module, to increase the extraction of multi-level information by the network, we firstly adopt a dual encoder structure and give information fusion in the decoder part. Secondly, different discriminators are used for infrared and visible images in order to highlight the thermal radiation information and key textures. The effectiveness of the method is verified by experiments on four datasets, and the results show that the method can effectively highlight the thermal radiation information and key texture details of the fused images, fully demonstrating its great potential and performance in solving the infrared and visible images fusion (IVF) problem.

关键词： Visualization Data integration Object detection sensor fusion Feature extraction Generators sensors

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HeAT - a distributed and GPU-accelerated Tensor Framework for Data Analytics 8

HeAT - a Distributed and GPU-accelerated Tensor Framework fo...

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8th ieee international conference on Big Data (Big Data)

作者： Goetz, Markus Debus, Charlotte Coquelin, Daniel Krajsek, Kai Comito, Claudia Knechtges, Philipp Hagemeier, Bjorn Tarnawa, Michael Hanselmann, Simon Siggel, Martin Basermann, Achim Streit, Achim German Aerosp Ctr Inst Software Technol SC Cologne Germany Forschungszentrum Julich Inst Rio & Geosci Agrosphere IBG 3 Julich Germany Forschungszentrum Julich FZJ Julich Supercomp Ctr JSC Julich Germany Karlsruhe Inst Technol KIT Steinbuch Ctr Comp SCC Karlsruhe Germany

ISBN: (纸本)9781728162515

To cope with the rapid growth in available data, the efficiency of data analysis and machine learning libraries has recently received increased attention. Although great advancements have been made in traditional array-based computations, most are limited by the resources available on a single computation node. Consequently, novel approaches must be made to exploit distributed resources, e.g. distributed memory architectures. To this end, we introduce IleAT, an array-based numerical programming framework for large-scale parallel processing with an easy-to-use NumPy-like API. HeAT utilizes PyTorch as a node-local eager execution engine and distributes the workload on arbitrarily large high-performance computing systems via MPI. It provides both low-level array computations, as well as assorted higher-level algorithms. With HeAT, it is possible for a NumPy user to take full advantage of their available resources, significantly I owering the bartier to distributed data analysis. When compared to similar frameworks, HeAT achieves speedups of up to two orders of magnitude.

关键词： IleAT Tensor Framework High-performance computing PyTorch NumPy Message Passing Interface CPU Rig Data Analytics Machine Learning Dask Model Parallelism Parallel Application Frameworks

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Shape Estimation Using Location-Unknown Distance sensors: A Curvature Based Approach 15

Shape Estimation Using Location-Unknown Distance Sensors: A ...

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15th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： Ikeuchi, Hiroki Saito, Hiroshi NTT Corp NTT Network Technol Labs Tokyo 1808585 Japan Univ Tokyo Grad Sch Informat Sci & Thechnol Tokyo 1138656 Japan

ISBN: (纸本)9781728105703

We discuss the shape estimation of a moving target object by using distributed simple sensors. Since we cannot always carefully design sensor locations or allocate global positioning systems (GPSs) to low-cost sensors, we usually assume that the locations of sensors as well as that of the target object are unknown. We propose a method of estimating the whole shape of a moving target object T that has curved segments. Our method analyzes continuous reports on the measured distance of T from distributed sensors and determines the sensing directions of sensors by deriving T's boundary characteristics, such as curvature, from sensing reports. On the basis of the obtained sensing directions, it estimates the whole shape of T. We conducted numerical simulations and evaluated our method using simple geometric and realistic vehicle-shaped objects.

关键词： sensor network distance sensor distributed sensor shape estimation random placement unknown location geometry differential geometry curvature

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Decentralized electronic voting system using Hyperledger Fabric

Decentralized electronic voting system using Hyperledger Fab...

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ieee international conference on Services computing (SCC)

作者： Aneta Poniszewska-Marań da Stanislaw Rojek Michal Pawlak Institute of Information Technology Lodz University of Technology &#x0141 &#x00F3 d&#x017A Poland

ISBN: (数字)9781665481465

ISBN: (纸本)9781665481472

Voting is an indispensable part of life in the current society. Everyone is part of social groups of different size and in most of them can influence important decisions by casting a vote. The development of technology makes it possible to support the voting process. The technology can be used during the process of checking and counting votes, as well as during *** paper presents the development process of e-voting system named BlockVote. System contains three components: Hyperledger Fabric network, middleware application and user interface. Hyperledger Fabric is blockchain network, in which two smart contracts EVotingContract and CodesContract were installed. Those smart contracts provide logic for voting. The middleware application enables communication between user interface and blockchain network. BlockVote allows to conduct voting that may consist of multiple closed questions. Users can cast a vote by entering the voting code and voting ID number. User receives confirmation of a vote in the form of transaction number, by means of which he can verify that his vote has been saved in the blockchain network. The voting history along with each vote cast is saved in the blockchain network.

关键词： Electronic voting systems Codes distributed ledger Smart contracts systems architecture User interfaces Fabrics

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Evaluation of the interest of an extra-slot for a grouped polling-selecting method 39

Evaluation of the interest of an extra-slot for a grouped po...

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39th ieee international Performance computing and Communications conference (IPCCC)

作者： Sidibe, Guereguin Der Sylvestre Bidaud, Raphael Servajean, Marie-Francoise Hakem, Nadir Misson, Michel Univ Clermont Auvergne LIMOS CNRS Aubiere France Univ Quebec Abitibi Temiscamingue LRTCS Valdor PQ Canada

ISBN: (纸本)9781728198293

Switched beam antennas (SBA) have been shown to offer many advantages when used in confined and obstructed environments that represent a difficult radio propagation environment. However, when SBA are used in wireless network, the popular contention-based medium access control protocol such as ieee 802.15.4 MAC is no longer effective. Furthermore, the contention based nature of ieee 802.15.4 MAC makes it not suitable for deterministic transmissions. In order to have a good compromise between range, data rate and deterministic behavior, in this paper, we propose data collection schemes based on polling-selecting strategies for low latency deterministic networked (LLDN) systems where the sink is equipped with a SBA and sensor nodes with usual omnidirectional antennas. Our solution is based on ieee 802.15.4 frame exchanges in star topology. We present an analytical model to evaluate the benefit of using an extra slot in a collection scheme based on polling strategy. Several simulations were conducted to validate the analytical model and show that using an extra slot in a collection scheme based on polling strategy improves the frame delivery rate.

关键词： ieee 802.15.4 Low latency deterministic network (LLDN) WSN Medium access control (MAC) TDMA Switched beam antenna

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MicroRAS: Automatic Recovery in the Absence of Historical Failure Data for Microservice systems 13

MicroRAS: Automatic Recovery in the Absence of Historical Fa...

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13th ieee/ACM international conference on Utility and Cloud computing (UCC)

作者： Wu, Li Tordsson, Johan Acker, Alexander Kao, Odej Elastisys AB Umea Sweden TU Berlin Distributed & Operating Syst Grp Berlin Germany Umea Univ Dept Comp Sci Umea Sweden

ISBN: (纸本)9780738123943

Microservices represent a popular paradigm to construct large-scale applications in many domains thanks to benefits such as scalability, flexibility, and agility. However, it is difficult to manage and operate a microservice system due to its high dynamics and complexity. In particular, the frequent updates of microservices lead to the absence of historical failure data, where the current automatic recovery methods fail short. In this paper, we propose an automatic recovery method named MicroRAS, which requires no historical failure data, to mitigate performance issues in microservice systems. MicroRAS is a model-driven method that selects the appropriate recovery action with a trade-off between the effectiveness and recovery time of actions. It estimates the effectiveness of an action in terms of its effects of recovering the pinpointed faulty service and its effects of interfering with other services. The estimation of action effects is based on a system-state model represented by an attributed graph that tracks the propagation of effects. For the experimental evaluation, several types of anomalies are injected into a microservice system based on Kubernetes, which also serves a real-world workload. The corresponding benchmarks show that the actions selected by MicroRAS can recover the faulty services by 94.7%, and reduce the interference to other services by at least 44.3% compared to baseline methods.

关键词： automatic recovery microservices performance issues cloud computing Kubernetes

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A Software Architecture to enable Self-Organizing, Collaborative IoT Ressource Networks 5

A Software Architecture to enable Self-Organizing, Collabora...

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5th international conference on Fog and Mobile Edge computing (FMEC)

作者： Lewandowski, Tim Henze, Dominic Sauer, Markus Nickles, Jochen Bruegge, Bernd Tech Univ Munich Chair Appl Software Engn Munich Germany Siemens AG Corp Technol Munich Germany

ISBN: (纸本)9781728172163

Since recent years, the industrial world is facing a significant change from components and systems that are designed and configured for one well-analyzed scenario using well-established technologies to a demand for highly dynamic systems that continuously introduce the latest technologies and are capable of handling ever-changing use case environments. Thus, there is a need for new approaches on how to design and setup such systems. One of these approaches is Collaborative IoT, which focuses on researching the necessary designs, infrastructure, and technology to build ecosystems of loosely coupled, autonomous systems that interact in an ad-hoc fashion and establish service compositions and new distributed applications on demand. This paper presents a software architecture design for Industrial IoT systems to approach these targets as well as a reference implementation showing the feasibility of the architectural design in a Collaborative IoT smart factory scenario. The developed AiB architecture enables heterogeneous IoT systems to form task execution ecosystems that dynamically address new incoming tasks by creating service compositions across participating devices, which were not defined during design time.

关键词： Industrial IoT distributed computing Fog computing Edge computing Collaborative Autonomous systems

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Machine learning in wireless sensor networks: A retrospective 6

Machine learning in wireless sensor networks: A retrospectiv...

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6th international conference on Parallel, distributed and Grid computing, PDGC 2020

作者： Mehta, Aina Sandhu, Jasminder Kaur Sapra, Luxmi Chitkara University Institute of Engineering and Technology Chitkara Univeristy Punjab India

ISBN: (纸本)9781728171326

Wireless sensor Networks consist of spatially dispersed autonomous sensor nodes which collect data from the environment and forward to the other gateway for processing. These network controls the dynamic environment that changes frequently with time. This effectual behavior is created or initialized by outward parameters such as temperature, sound, light, events. To adjust with such situations these networks follow Machine Learning techniques. In this paper, a review on the Machine Learning techniques that can be applied on these networks is presented. These networks are the most trending technologies for some real applications because of its features such as low-cost, tiny and mobility. Further, a relative guide to the network designers is suggested for developing appropriate Machine Learning solutions for requisite application. © 2020 ieee.

关键词： Decision trees

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DiHi: distributed and Hierarchical Performance Modeling of Multi-VM Cloud Running Applications 22

DiHi: Distributed and Hierarchical Performance Modeling of M...

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22nd ieee international conference on High Performance computing and Communications, 18th ieee international conference on Smart City and 6th ieee international conference on Data Science and systems, HPCC-SmartCity-DSS 2020

作者： Moradi, Hamidreza Wang, Wei Zhu, Dakai The University of Texas at San Antonio United States

ISBN: (纸本)9781728176499

Performance fluctuation of cloud running applications, due to collocations of different tenants on the same machine, is one of the cloud users' concerns. To alleviate users' concerns with insightful information, performance modeling and prediction of their applications is deemed necessary. In this paper, we propose two hierarchical and a monolithic performance modeling and prediction frameworks for multi-VM applications running on clouds. Hierarchical frameworks have been considered to distribute the required processing power for performance modeling and prediction over a group of collaborating VMs for better scalability, and to reduce the load of transferring unprocessed profiling data. Several unsupervised learning algorithms and existing single-VM models have been incorporated into the hierarchical frameworks to evaluate their effects on models' accuracy. Then, the results are compared with a baseline approach where the most intuitive monolithic framework requires the accumulation of all profiling data on a central VM. We have considered a comprehensive set of micro-benchmarks to probe the contention in various resources of all collaborating VMs. Then, using the proposed frameworks, the experienced contention levels by each VM and the overall performance of the applications are modeled and predicted. The results of our experiments in a private and two public clouds show that the distributed and hierarchical frameworks can predict the overall applications' performance effectively with comparable accuracy to the monolithic framework with an average prediction error of 5% for different cluster sizes and clouds. © 2020 ieee.

关键词： Forecasting

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Towards a new paradigm for managing computing continuum applications

Towards a new paradigm for managing computing continuum appl...

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ieee international conference on Cognitive Machine Intelligence (CogMI)

作者： Víctor Casamayor Pujol Philipp Raith Schahram Dustdar Distributed Systems Group TU Wien Vienna Austria

ISBN: (纸本)9781665416221

“computing continuum” systems are expected to sculpt our future society through a manifold of applications, most of them leveraging artificial intelligence systems. How-ever, their inherent complexity, brought by their dependency on their underlying infrastructure, requires to propose new methodologies for managing them. The methodologies that are now in place are founded on the first Internet systems and they are not able to cope with the complexity of these systems. In this article we first develop the idea of the complexity on these “computing continuum” systems that have Edge Intelligence applications running on them. Then we present our vision on how to represent and manage these emerging systems. Based on a use case, we highlight the system's inherent complexity and we finally sketch how our vision would work on the showcased system.

关键词： Manifolds Directed acyclic graph Adaptive systems conferences distributed databases Markov processes Complexity theory

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