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检索条件"任意字段=Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems"

共 1614 条记录，以下是151-160 订阅

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S2CE: A hybrid cloud and edge orchestrator for mining exascale distributed streams 21

S2CE: A hybrid cloud and edge orchestrator for mining exasca...

引用

15th acm international conference on distributed and event-based systems, DEBS 2021

作者： Kourtellis, Nicolas Herodotou, Herodotos Grzenda, MacIej Wawrzyniak, Piotr Bifet, Albert Telefonica Research Barcelona Spain Cyprus University of Technology Limassol Cyprus Warsaw University of Technology Warsaw Poland Lodz University of Technology Lodz Poland Ai Institute University of Waikato Hamilton New Zealand Ltci Telecom Paris IP-Paris Paris France

ISBN: (纸本)9781450385558

the explosive increase in volume, velocity, variety, and veracity of data generated by distributed and heterogeneous nodes such as IoT and other devices, continuously challenge the state of art in big data processing platforms and mining techniques. Consequently, it reveals an urgent need to address the ever-growing gap between this expected exascale data generation and the extraction of insights from these data. To address this need, this position paper proposes Stream to Cloud and Edge (S2CE), a first of its kind, optimized, multi-cloud and edge orchestrator, easily configurable, scalable, and extensible. S2CE will enable machine and deep learning over voluminous and heterogeneous data streams running on hybrid cloud and edge settings, while offering the necessary functionalities for practical and scalable processing: data fusion and preprocessing, sampling and synthetic stream generation, cloud and edge smart resource management, and distributed processing. © 2021 acm.

关键词： Information management

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Understanding the Relation of User and News Representations in Content-based Neural News Recommendation 10

Understanding the Relation of User and News Representations ...

引用

Joint 10th international Workshop on News Recommendation and Analytics and the 3rd international Workshop on Investigating Learning During Web Search, INRA + IWILDS 2022 co-located with the 45th international acm SIGIR conference on Research and Development in Information Retrieval, SIGIR 2022

作者： Möller, Lucas Padó, Sebastian Institute for Natural Language Processing University of Stuttgart Germany

A number of models for neural content-based news recommendation have been proposed. However, there is limited understanding of the relative importances of the three main components of such systems (news encoder, user encoder, and scoring function) and the trade-offs involved. In this paper, we assess the hypothesis that the most widely used means of matching user and candidate news representations is not expressive enough. We allow our system to model more complex relations between the two by assessing more expressive scoring functions. Across a wide range of baseline and established systems this results in consistent improvements of around 6 points in AUC. Our results also indicate a trade-off between the complexity of news encoder and scoring function: A fairly simple baseline model scores well above 68% AUC on the MIND dataset and comes within 2 points of the published state-of-the-art, while requiring a fraction of the computational costs. © 2022 Copyright for this paper by its authors.

关键词： Economic and social effects

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Synchronised Power Scheduling of Widely distributed Refrigerators using IoT 10

Synchronised Power Scheduling of Widely Distributed Refriger...

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10th international conference on Smart Cities and Green ICT systems (SMARTGREENS)

作者： Sabegh, M. R. Zavvar Bingham, C. M. Univ Lincoln Sch Engn Lincoln England

ISBN: (纸本)9789897585128

the paper proposes an IoT controlled platform to remotely monitor and control appliances in the residential sector. An IP-based synchronized wireless mesh network is implemented through IoT hardware (based on a NodeMCU) and Google Sheets to monitor and schedule the operation of aggregated domestic refrigerators under a Model Predictive Control (MPC) scheme. Benefits afforded by the proposed technique are investigated through experimental trials from VonShef 13/291 (50W), iGENIX IG 3920 (55W) and Russell Hobbs RHCLRF17B (50W) domestic refrigerators sited in three different domestic locations in the city of Lincoln, UK. Results demonstrate the ability to monitor and control widely distributed networks of refrigerators and adaptively schedule the appliances to reduce peak operational loads and facilitate Demand Side Response (DSR). Further widespread expansion of the proposed technique would allow for a rapidly deployed regional DSR strategy to aid grid stability. Ultimately the underlying principles also could be used for the co-ordinated scheduling of other distributed appliances and equipment, both domestic and industrial.

关键词： Internet of things (IoT) IP-based Synchronized Wireless Mesh Network Model Predictive Control (MPC) Smart Home

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Data Science Driven Methods for Sustainable and Failure Tolerant Edge systems 22

Data Science Driven Methods for Sustainable and Failure Tole...

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13th Annual acm/SPEC international conference on Performance Engineering (ICPE)

作者： Brandic, Ivona Vienna Univ Technol Vienna Austria

ISBN: (纸本)9781450391436

Nowadays we experience a paradigm shift in our society, where every item around us is becoming a computer facilitating life-changing applications like self-driving cars, tele-medicine, precision agriculture or virtual reality. On one hand, for the execution of such resource demanding applications we need powerful IT facilities. On the other hand, the requirements often include latencies below 100 ms or even below 10 ms - what is called "tactile internet". To facilitate low latency computation has to be placed in the vicinity of the end users by utilizing the concept of Edge Computing. In this talk we explain the challenges of Edge systems in combination with tactile internet. We discuss the recent problems of geographically distributed machine learning applications and novel approaches to balance competing priorities like the energy efficiency and the staleness of the machine learning models. Available failure resilience mechanisms designed for Cloud computing or generic distributed systems cannot be applied to Edge systems due to timeliness, hyper heterogeneity and resource scarcity. therefore, we discuss a novel machine learning based mechanism that evaluates the failure resilience of a service deployed redundantly on the edge infrastructure. Our approach learns the spatiotemporal dependencies between edge server failures and combines them with the topological information to incorporate link failures by utilizing the concept of the Dynamic Bayesian Networks (DBNs). eventually, we infer the probability that a certain set of servers fails or disconnects concurrently during service runtime.

关键词： edge computing geographically distributed machine learning dynamic Bayesian Networks

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Learning-based event-triggered Adaptive Optimal Output Regulation of Linear Discrete-time systems 10

Learning-based Event-triggered Adaptive Optimal Output Regul...

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10th IEEE Data Driven Control and Learning systems conference, DDCLS 2021

作者： Zhao, Fuyu Gao, Weinan Liu, Tengfei Jiang, Zhong-Ping State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China College of Engineering and Science Florida Institute of Technology Department of Mechanical and Civil Engineering MelbourneFL32901 United States New York University Six MetroTech Center Department of Electrical and Computer Engineering BrooklynNY11201 United States

ISBN: (纸本)9781665424233

In this paper, a data-driven event-triggered output-feedback control approach is proposed to solve the problem of adaptive optimal output regulation for uncertain discrete-time linear systems when only the output information is available. A crucial strategy is to develop a novel co-design scheme for the event-triggering mechanism and the data-driven optimal controller. theoretical analysis and an application to a LCL coupled inverter-based distributed generation system demonstrate the effectiveness of the proposed learning-based, event-triggered, adaptive optimal controller design with output-feedback. © 2021 IEEE.

关键词： Digital control systems

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Descriptor based consensus for blockchain transactions 21

Descriptor based consensus for blockchain transactions

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15th acm international conference on distributed and event-based systems, DEBS 2021

作者： Painter, Zachary Cook, Victor Peterson, Christina Dechev, Damian Fabriik Alpha Limited London United Kingdom Department of Computer Science University of Central Florida OrlandoFL United States

ISBN: (纸本)9781450385558

Blockchain networks use consensus mechanisms so participants can exchange transactions without the need to rely on a trusted third party. Consensus mechanisms using Proof of Work burn significant energy to select a block miner and the delay limits performance. Other consensus mechanisms such as Proof of Stake or Practical Byzantine Fault Tolerance still designate a single validator to append a block to the chain, preventing blocks from being built and published in parallel. In this paper we introduce a new consensus mechanism, Proof of Descriptor, enabling clients to work together to publish blockchain transactions using a descriptor object which stores information on the cooperative parallel execution of transactions. Proof of Descriptor consensus allows commutative transactions to be mined individually. It does not require a leader to propose the next block, enabling clients to cooperate on completing transactions, assembling blocks and publishing them. We demonstrate that our approach is less prone to attack since it is not vulnerable to a malicious leader, while simulations show a potential 20x improvement over the fastest sequential blockchain, Solana. © 2021 acm.

关键词： Blockchain

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Genetic Programming based Iterative Improvement Algorithm for HW/SW Cosynthesis of Distributted Embedded systems 10

Genetic Programming based Iterative Improvement Algorithm fo...

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10th international conference on Sensor Networks (SENSORNETS)

作者： Gorski, Adam Ogorzalek, Maciej Jagiellonian Univ Cracow Dept Informat Technol Prof Stanislawa Lojasiewicza 11 Krakow Poland

ISBN: (纸本)9789897584893

In this work we present a novel genetic programming based iterative improvement approach for hardware/software cosynthesis of distributed embedded systems. the approach starts from a ready solution which is an embryo of a genotype. Other nodes in the genotypes are chromosomes. the chromosomes contain system refinement options. the final solution is obtained after evolution process and mapping genotype to phenotype. Unlike existing genetic programming iterative improvement methodologies our algorithm starts from randomly generated system. therefore the search space is not constrained by any initial condition. It is also easier for the algorithm to escape local minima of optimizing parameters.

关键词： Embedded systems Architecture Hardware/Software Co-Synthesis Genetic Programming

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IEEE 10th Joint international Information Technology and Artificial Intelligence conference, ITAIC 2022

IEEE 10th Joint International Information Technology and Art...

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10th IEEE Joint international Information Technology and Artificial Intelligence conference, ITAIC 2022

ISBN: (纸本)9781665422079

the proceedings contain 495 papers. the topics discussed include: improved edge detection algorithm for canny operator;overview of spectrum sharing technology;EEG classification based on deep learning;research on topology control method of dynamic space-based TT&C network based on time-space graph;u-net fundus retinal vessel segmentation method based on multi-scale feature fusion;resolve from flight conflicts at the same flight level;research on information transmission capability evaluation of information processing system based on fuzzy mathematics comprehensive evaluation method;short-term wind power forecasting model based on stacking fusion learning;another algorithm to determine if it is a state transfer matrix;dose nonuniformity estimation method for scientific test of cobalt source device;research on the overall transformation scheme of the first access network of dispatching data network of state grid Weifang power supply company;deep Kalman-based trajectory estimation of moving target from satellite images;adaptive event-triggered cooperative tracking control with full-state constraints for a class of nonlinear time-varying multi-agent systems;and simulation modeling and software implementation of optical fiber and space channel in quantum secure communication.

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Make Federated Learning a Standard in Robotics by Using ROS2 23

Make Federated Learning a Standard in Robotics by Using ROS2

引用

proceedings of the IEEE/acm 10th international conference on Big Data Computing, Applications and Technologies

作者： Roberto Marino Lorenzo Carnevale Maria Fazio Massimo Villari Department of Mathematical and Computer Sciences Physical Sciences and Earth Science University of Messina Messina IT Department of Mathematical and Computer Sciences Physical Sciences and Earth Science University of Messina Messina Italy

ISBN: (纸本)9798400704734

the use of the Federated Learning paradigm could be disruptive in robotics, where data are naturally distributed among teams of agents and centralizing them would increase latency and break privacy. Unfortunately there are a lack of robot oriented framework for federated learning that use state of the art machine learning libraries. ROS2 (Robot Operating systems) is a standard de-facto in robotics for building up teams of robots in a multi-node fully distributed manner. In this paper we presents the integration of ROS2 with PyTorch allowing an easy training of a global machine learning model starting from a set of local datasets. We present the architecture, the used methodology and finally we discuss the experimentation results over a well-known public dataset.

关键词： federated learning robotics ROS PyTorch distributed intelligence machine learning

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the Study of Transition to the Isolated Operation of Power Supply systems with distributed Generation Plants and High Power Energy Storage Units 10

The Study of Transition to the Isolated Operation of Power S...

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10th international conference on Smart Cities and Green ICT systems (SMARTGREENS)

作者： Bulatov, Yuri N. Kryukov, Andrey, V Suslov, Konstantin, V Bratsk State Univ Dept Elect Power & Elect Engn Bratsk Russia Irkutsk State Transport Univ Dept Transport Elect Power Irkutsk Russia Irkutsk Natl Res Tech Univ Dept Power Supply & Elect Engn Irkutsk Russia

ISBN: (纸本)9789897585128

the development of power engineering, under current conditions, is aimed at the use of distributed generation plants in power supply systems located in immediate proximity from power consumers. the article deals with power supply system with turbo generator plant and high power energy storage unit. Description of a power supply system model with turbo generator plant, energy storage unit and asynchronous load is provided, and modeling results of power supply system transition to the isolated operating mode. the model of the power supply system under study was carried out in the MATLAB environment using the Simul ink and SimPowerSvstems simulation packages. In work is a description of the PSS model used IN ith DG plant and ESU, as well as the simulation results. based on the computer simulation results the conclusion, that use of prognostic controllers turbo generator plant allows improving the damping properties of the system when switching to an isolated mode of operation.

关键词： distributed Generation Plants Power Supply systems Energy Storage Isolated Mode Asynchronous Load Automatic Excitation Controller Automatic Speed Controller Simulation

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