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

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Comparison of Cloud Architectures for Mobile sensor Optimization Problem Implementation 15

Comparison of Cloud Architectures for Mobile Sensor Optimiza...

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ieee 15th international conference of System of systems Engineering (SoSE)

作者： Ackels, Sean Benavidez, Patrick Jamshidi, Mo Univ Texas San Antonio Dept Elect & Comp Engn ACE Labs San Antonio TX 78249 USA

ISBN: (纸本)9781728180502

The field of swarm robotics has continued to grow in recent years, branching into new fields that require more complex algorithms to solve and faster response times to control. Fields such as cloud and fog computing have been used to counter this first issue, allowing agents to use a network to access systems with much higher computational abilities, but this comes at the cost of increased latency. New architectures such as the Lambda and Kappa architectures have been developed to remedy this issue, allowing for cloud computers to be used while not sacrificing response times. This paper focuses on comparing three different architectures to assess their performance on a simulated robotic swam to solve the mobile sensor optimization problem. These three architectures are a traditional robot, the Lambda architecture, and the Kappa architecture. These systems are compared based off their latency and the runtimes of different algorithms in each implementation.

关键词： Cloud computing Lambda Architecture Kappa Architecture Radial Basis Function Mobile sensor Optimization Problem Swarm Robotics

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Supercomputer Engineering for Supporting Decision-making on Energy systems Resilience 14

Supercomputer Engineering for Supporting Decision-making on ...

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14th ieee international conference on Application of Information and Communication Technologies (AICT)

作者： Bychkov, Igor Feoktistov, Alexander Gorsky, Sergey Edelev, Alexei Sidorov, Ivan Kostromin, Roman Fereferov, Evgeniy Fedorov, Roman Russian Acad Sci Matrosov Inst Syst Dynam & Control Theory Siberian Branch Irkutsk Russia Russian Acad Sci Melentiev Energy Syst Inst Siberian Branch Irkutsk Russia

ISBN: (纸本)9781728173863

We propose a new approach to creating a subject-oriented distributed computing environment. Such an environment is used to support decision-making in solving relevant problems of ensuring energy systems resilience. The proposed approach is based on the idea of advancing and integrating the following important capabilities in supercomputer engineering: continuous integration, delivery, and deployment of the system and applied software, high-performance computing in heterogeneous environments, multi-agent intelligent computation planning and resource allocation, big data processing and geo-information servicing for subject information, including weakly structured data, and decision-making support. This combination of capabilities and their advancing are unique to the subject domain under consideration, which is related to combinatorial studying critical objects of energy systems. Evaluation of decision-making alternatives is carrying out through applying combinatorial modeling and multi-criteria selection rules. The Orlando Tools framework is used as the basis for an integrated software environment. It implements a flexible modular approach to the development of scientific applications (distributed applied software packages).

关键词： energy systems resilience decision-making supercomputer engineering distributed applied software packages

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Kalman Filter Based sensor Fusion for Omnidirectional Mechatronic System 35

Kalman Filter Based Sensor Fusion for Omnidirectional Mechat...

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35th international conference on Power Electronics and Electrical Drives, EDPE 2021

作者： Korotaj, Blaž Novoselnik, Branimir Baotić, Mato Department of Control and Computer Engineering Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

The paper describes the sensor fusion for the newly developed omnidirectional mechatronic system. To that end, the kinematic model of the platform and the chosen configuration of omnidirectional Mecanum wheels is described, as well as the principle of operation of all system sensors. The expressions are given for a discrete linear Kalman filter that fuses measurements of a magnetometer and gyroscope, and for a discrete extended Kalman filter that estimates position and orientation of the platform using additional accelerometer measurements. To be able to express the measurement equation four additional states are added to the system model. The developed sensor fusion algorithm was implemented in MATLAB/Simulink programming environment, and very accurate simulation results are reported for estimation of position and orientation of the system. Finally, the real time experimental results are reported for a prototype of the omnidirectional mobile mechatronic system. ©2021 ieee.

关键词： Discrete extended Kalman filter Mobile mechatronic system Omnidirectional drive sensor fusion State estimation

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Agent-Navigable Dynamic Graph Construction and Visualization over distributed Memory 8

Agent-Navigable Dynamic Graph Construction and Visualization...

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

作者： Gilroy, Justin Paronyan, Satine Acoltzi, Jonathan Fukuda, Munehiro Univ Washington Bothell Comp & Software Syst Bothell WA 98011 USA

ISBN: (纸本)9781728162515

Some graph analyses, such as social network and biological network, need large-scale graph construction and maintenance over distributed memory space. distributed data-streaming tools, including MapReduce and Spark, restrict some computational freedom of incremental graph modification and run-time graph visualization. Instead, we take an agent-based approach. We construct a graph from a scientific dataset in CSV, tab, and XML formats;dispatch many reactive agents on it;and analyze the graph in the form of their collective group behavior: propagation, flocking, and collision. The key to success is how to automate the run-time construction and visualization of agent-navigable graphs mapped over distributed memory. We implemented this distributed graph-computing support in the multi-agent spatial simulation (MASS) library, coupled with the Cytoscape graph visualization software. This paper presents the MASS implementation techniques and demonstrates its execution performance in comparison to MapReduce and Spark, using two benchmark programs: (1) an incremental construction of a complete graph and (2) a KD tree construction.

关键词： multi-agent systems agent-based modeling data analysis data visualization parallel programming

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Design and Implementation of distributed Fault-tolerant Computer Communication Software of Deterministic Communication Based on TTE

Design and Implementation of Distributed Fault-tolerant Comp...

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2020 ieee international conference on Power, Intelligent computing and systems, ICPICS 2020

作者： Guo, Yong Lu, Shuai Dai, Xiaodi Duan, Haijun Xi'an Aeronautics Computing Technique Research Institute Xi'an Shaanxi710065 China

ISBN: (纸本)9781728198736

The distributed fault-tolerant computer technology of deterministic communication takes the needs of a new generation of IVMS as background in this paper, the system architecture design and software architecture of distributed fault-tolerant computer are studied, and one kind of communication software based on VxWorks653 partition operating system is designed and implemented, moreover, it has been practically applied in engineering, and it can meet the communication needs of big data and high-performance in avionics applications after function and performance verification. This communication protocol software is implemented with layered architecture, which is conducive to cross-platform migration, software reuse, and subsequent hardware upgrades. © 2020 ieee.

关键词： Computer software reusability

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distributed macroscopic traffic simulation with Open Traffic Models 23

Distributed macroscopic traffic simulation with Open Traffic...

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23rd ieee international conference on Intelligent Transportation systems (ITSC)

作者： Gomes, Gabriel Ugirumurera, Juliette Li, Xiaoye S. Univ Calif Berkeley Inst Transportat Studies Berkeley CA 94720 USA Natl Renewable Energy Lab Computat Sci Ctr Denver CO USA Lawrence Berkeley Natl Lab Computat Res Div Berkeley CA USA

ISBN: (纸本)9781728141497

This paper presents OTM-MPI, an extension of the Open Traffic Models platform (OTM) for running macroscopic traffic simulations in high-performance computing environments. OTM-MPI represents the first open-source, distributed-memory, macroscopic simulation model developed for modern high performance parallel machines and large networks. Macroscopic simulations are appropriate for studying regional traffic scenarios when aggregate trends are of interest, rather than individual vehicle traces. They are also appropriate for studying the routing behavior of classes of vehicles, such as app-informed vehicles. The network partitioning was performed with METIS. Inter-process communication was done with MPI (message-passing interface). Results are provided for two networks: one realistic network which was obtained from Open Street Maps for Chattanooga, TN, and another larger synthetic grid network. The software recorded a speedups of 198x using 256 cores for Chattanooga, and 475x with 1,024 cores for the synthetic network.

关键词： Traffic simulation Parallel simulation Macroscopic traffic simulation Parallel computing

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Fault Detection Mechanism of a Predictive Maintenance System Based on Autoregressive Integrated Moving Average Models 16th

Fault Detection Mechanism of a Predictive Maintenance System...

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16th international Symposium on distributed computing and Artificial Intelligence (DCAI)

作者： Fernandes, Marta Canito, Alda Corchado, Juan Manuel Marreiros, Goreti Polytech Porto ISEP IPP GECAD Res Grp Intelligent Engn & Comp Adv Innovat Porto Portugal Univ Salamanca USAL BISITE Res Ctr Salamanca Spain

ISBN: (纸本)9783030238872;9783030238865

The industrial world is amid a revolution, titled Industry 4.0, which entails the use of IoT technologies to enable the exchange of information between sensors, industrial machines and end users. A major issue in many industrial sectors is production inefficiency, with process downtime representing a loss for companies. Predictive maintenance, whereby maintenance is performed only when needed and before a failure occurs, has the potential to substantially reduce costs. This paper describes the fault detection mechanism of a predictive maintenance system developed for the metallurgic industry. Considering no previous information about faults is available, learning happens in an unsupervised manner. Imminent faults are predicted by estimating autoregressive integrated moving average models using real-world sensor data obtained from monitoring different machine components and parameters. The models' outputs are fused to assess the significance of an anomaly (or anomalies) along the time domain and determine how likely a fault is to occur, with alarms being issued when the prospect of a fault is high enough.

关键词： Predictive maintenance Anomaly detection ARIMA models sensor data

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Implementation of distributed Crawler System Based on Spark for Massive Data Mining 5

Implementation of Distributed Crawler System Based on Spark ...

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ieee 5th international conference on Computer and Communication systems (ICCCS)

作者： Liu, Feng Xin, Wang Hebei GEO Univ Shijiazhuang Hebei Peoples R China Hebei Software Testing Ctr Shijiazhuang Hebei Peoples R China

ISBN: (纸本)9781728161365

In the era of rapid development of Internet technology and increasing social needs of people, web crawlers have been maturely applied to major search engines and search fields. By using Spark's RDD elastic computing architecture and task assignment algorithm, this paper integrates the architecture of Spark-based distributed crawler system, gives the corresponding framework diagram, and introduces the distributed framework system in detail. Through this Spark-based distributed crawler system we can solve the problem of insufficient resource utilization and low collection efficiency, and then solve the contradiction between the current explosive growth of data scale and the speed of obtaining information.

关键词： spark distributed web crawler framework

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Design and research of a distributed and scalable information platform for electric power sensing 9

Design and research of a distributed and scalable informatio...

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9th ieee Joint international Information Technology and Artificial Intelligence conference, ITAIC 2020

作者： Zeng, Pengfei Liang, Yun Tian, Wenfeng Sun, Xiaoyan Global Energy Interconnection Research Institute Co.Ltd. Beijing China Elec. Power Intelligent Sensing Technology and Application State Grid Corporation Joint Laboratory Beijing China

The development of power systems has called higher requirements for sensor information platforms, and sensor information platforms have become one key supporting technology for efficient and stable operation of power grids. This article first analyzes the current IoT reference architecture and the development trend of IoT platforms. Then, a distributed sustainable integrated architecture sensor information platform is proposed to cater to the sensor requirements of the current power grid. Specifically, for the architecture, the distributed design and continuous integration design of the platform are introduced in detail. Finally, based on the designed architecture in this article, the practical work carried out by the information platform is introduced. This platform can be used for partial discharge detection of power equipment, providing edge intelligent computing support for the detection and analysis of radio frequency pulse signals. © 2020 ieee.

关键词： Internet of things

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Detection of Faulty Nodes in distributed Environment using Machine Learning 3

Detection of Faulty Nodes in Distributed Environment using M...

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3rd international conference on Advances in computing, Communication Control and Networking, ICAC3N 2021

作者： Gaykar, Reshma S. Khanaa, V. Joshi, S.D. Bharath Institute of Higher Education and Research Department of Computer Science and Engineering Chennai India Bharath Institute of Higher Education and Research Information Center Chennai India Bharati Vidyapeeth University Faculty of Engineering and Technology Pune India

ISBN: (纸本)9781665438117

Faulty nodes are expected to have a significant effect on the performance of Big Data systems. The cause of discharges, on the other hand, is a complex issue. The previous work has mostly focused on identifying Stragglers, optimizing the quality of programming, and root cause investigation. These methods can't offer useful information unless they can assist users automate their services. We are developing a framework that determines when there will be stragglers and must identify gaps to prevent those circumstances. This research proposed a dynamic log collection of heterogeneous virtual machine data and detect the faulty node based on execution performance using various parameters. We introduce multi-task learning mechanisms in this paper, which exchange knowledge between the different versions of nodes. The system first collects log data from available data nodes and applies an unsupervised machine learning technique to detect the straggler. Moreover, once a straggler has been detected by the learning algorithm, it tries mitigating such nodes instead of eliminating those nodes. The major benefit of this research is that the system can handle massive data with minimum data nodes or even system efficiently work with already heated nodes in a distributed environment. Our compositions absorb the shared context in our data, enhancing sweeping statement efficiency on minimal data, unlike naive inter learning frameworks. © 2021 ieee.

关键词： Balancing

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