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International Conference on parallel and distributed processing Techniques and Applications

作者： Eggen, M Pitts, G Trinity Univ Dept Comp Sci San Antonio TX 78284 USA

ISBN: (纸本)1892512459

In this modern era of knowledge explosion, one of the most exciting research areas is Artificial Intelligence (AI). In this paper we investigate more specifically the theory and design of a new area of AI labeled distributed intelligent agents, whose development encompasses a broad variety of applications. From robots to lunar landers, this technology holds great promise for providing intelligence to systems, that has either required human interaction or whose programming was so complex and expensive as to render it useless. The design specifications given in this paper will provide a research and development framework for a marriage of distributed artificial intelligence, intelligent agents, and distributed parallel processing called distributed Intelligent Agents (DIA).

关键词： artificial intelligence intelligent agent forward chaining backward chaining distributed and parallel processing

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A distributed AND parallel METHOD OF HYPERSPECTRAL COMPUTATIONAL IMAGING VIA COLLABORATIVE TUCKER3 TENSOR DECOMPOSITION

A DISTRIBUTED AND PARALLEL METHOD OF HYPERSPECTRAL COMPUTATI...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Zhang, Ling Wu, Zebin Sun, Jin Xu, Yang Wei, Zhihui Nanjing Univ Sci & Technol Sch Comp Sci & Engn Nanjing 210094 Peoples R China

ISBN: (数字)9781665427920

ISBN: (纸本)9781665427920

Hyperspectral computational imaging (HCI) is to reconstruct hyperspectral images (HSIs) based on the compressed signals collected by remote sensing and imaging systems. Collaborative Tucker3 tensor decomposition is beneficial for HCI models in reconstructing high-fidelity HSIs. However, the ever-increasing amount of compressed data leads to heavy computation burden for tensor decomposition-based HCI models, which may exceed the computing capacity of a single machine. For this reason, this paper proposes a Spark-based distributed and parallel HCI implementation via collaborative Tucker3 tensor decomposition. The proposed implementation decomposes the processing flow of the HCI algorithm into several stages, each of which can be processed in parallel on Spark. In addition, we develop parallel strategies for improving the performance of the redundant computational procedure and data storage procedure, respectively. Experimental results demonstrate that the parallel algorithm not only achieves high accuracy but also improves the computational efficiency when processing large-scale HSI datasets.

关键词： Hyperspectral computational imaging Spark distributed and parallel processing Tucker3 tensor decomposition

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Analysis and Real Implementation of a Cloud Infraestructure for Computing Laboratories Virtualization

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8th International Conference on Image processing and Communications (IP and C)

作者： Enrique Munoz-Exposito, Jose Perez de Prado, Rocio Garcia-Galan, Sebastian Rodriguez-Reche, Rafael Marchewka, Adam Univ Jaen Telecommun Engn Dept Alfonso X El Sabio 28 Linares Spain UTP Univ Sci & Technol Bydgoszcz Inst Telecommun & Comp Sci Bydgoszcz Poland

ISBN: (纸本)9783319238142;9783319238135

In this work, a cloud infrastructure is analysed and deployed to virtualize computing laboratories. Virtualization of computing resources allows the user to face a single computing interface whose capabilities are really offered by a cloud system that makes use of its processing capability on demand. The use of this proposed infrastructure reduces the cost of equipment investments as well as maintenance of real laboratories and further, it makes a more efficient use of available resources with a transparent user experience.

关键词： Computing virtualization Cloud computing OpenNebula distributed and parallel processing

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HYPERSPECTRAL AND MULTISPECTRAL IMAGE FUSION TARGET DETECTION BASED ON CLOUD-EDGE COLLABORATION

HYPERSPECTRAL AND MULTISPECTRAL IMAGE FUSION TARGET DETECTIO...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Hu, Jun Wu, Shanshan Wu, Zebin Zhang, Yi Plaza, Javier Plaza, Antonio Nanjing Univ Sci & Technol Sch Comp Sci & Engn Nanjing 210094 Peoples R China Nanjing Res Inst Elect Engn NRIEE Nanjing 210000 Peoples R China Univ Extremadura Dept Technol Comp & Commun Hyperspectral Comp Lab Caceres 10071 Spain

ISBN: (纸本)9798350320107

Hyperspectral target detection (HTD) aims to detect fine targets in hyperspectral images ( HSIs). The traditional HTD method in low-resolution hyperspectral image (LR-HSI) is incapable of detecting small targets, clearly and precisely. Accordingly, in this paper, we propose a hyperspectral and multispectral image fusion target detection method based on cloud-edge collaboration. In this method, LR-HSI is first employed for coarse detection with the output of some suspicious target areas. Afterwards, the hyperspectral images and multispectral images (HSI-MSI) fusion is performed on these areas for precise target detection. In order to ensure the efficiency of HTD, we intend to accelerate our method in parallel based on the cloud-edge collaborative architecture. Furthermore, we establish an optimization model and design a greedy strategy to achieve the optimal deployment for minimizing the shortest runtime on the cloud-edge collaborative architecture. The experimental results demonstrate that our proposed method can significantly improve the computational efficiency while ensuring the accuracy.

关键词： Hyperspectral and multispectral image fusion distributed and parallel processing Hyperspectral target detection Cloud-edge collaboration

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RIDE: real-time massive image processing platform on distributed environment

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EURASIP JOURNAL ON IMAGE AND VIDEO processing 2018年第1期2018卷 1页

作者： Kim, Yoon-Ki Kim, Yongsung Jeong, Chang-Sung Korea Univ Dept Elect Engn Seoul South Korea

As the demand for real-time data processing increases, a high-speed processing platform for large-scale stream data becomes necessary. For fast processing large-scale stream data, it is essential to use multiple distributed nodes. So far, there have been few studies on real-time massive image processing through efficient management and allocation of heterogeneous resources for various user-specified nodes on distributed environments. In this paper, we shall present a new platform called RIDE (Real-time massive Image processing platform on distributed Environment) which efficiently allocates resources and executes load balancing according to the amount of stream data on distributed environments. It minimizes communication overhead by using a parallel processing strategy which handles the stream data considering both coarse-grained and fine-grained parallelism simultaneously. Coarse-grained parallelism is achieved by the automatic allocation of input streams onto partitions of broker buffer each processed by its corresponding worker node, and maximized by adaptive resource management which adjusts the number of worker nodes in a group according to the frame rate in real time. Fine-grained parallelism is achieved by parallel processing of task on each worker node and maximized by allocating heterogeneous resources such as GPU and embedded machines appropriately. Moreover, it provides a scheme of application topology which has a great advantage for higher performance by configuring the worker nodes of each stage using adaptive heterogeneous resource management. Finally, it supports dynamic fault tolerance for real-time image processing through the coordination between components in our system.

关键词： Real-time Image processing distributed and parallel processing Heterogeneous computing

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Complexity Analysis of Multilayer Perceptron Neural Network Embedded into a Wireless Sensor Network

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Procedia Computer Science 2014年 36卷 192-197页

作者： Gursel Serpen Zhenning Gao Electrical Engineering and Computer Science University of Toledo Toledo Ohio 43606 USA

This paper presents computational and message complexity analysis for a multi-layer perceptron neural network, which is implemented in fully distributed and parallel form across a wireless sensor network. Wireless sensor networks offer a promising platform for parallel and distributed neurocomputing as well as potentially benefiting from artificial neural networks for enhancing their adaptation abilities and computational intelligence. Multilayer perceptron (MLP) neural networks are generic function approximators and classifiers with countless domain-specific applications as reported in the literature. Accordingly, embedding a multilayer perceptron neural network in a wireless sensor network in parallel and distributed mode offers synergy and is very promising. Accordingly, assessing the computational and communication complexity of such hybrid designs, namely an artificial neural network such as a multilayer perceptron network embedded within a wireless sensor network, of interest. This paper presents bounds and results of empirical study on the time, space and message complexity aspects of a wireless sensor network and multilayer perceptron neural network design.

关键词： distributed and parallel processing multilayer perceptron neural network wireless sensor network computational complexity communication complexity

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Adaptive Information Visualization for Maritime Traffic Stream Sensor Data with parallel Context Acquisition and Machine Learning

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SENSORS 2019年第23期19卷 5273-5273页

作者： Kim, Kwang-il Lee, Keon Myung Jeju Natl Univ Dept Marine Ind & Maritime Police Jeju 64343 South Korea Chungbuk Natl Univ Dept Comp Sci Cheongju 28644 South Korea

Excessive information significantly increases the mental burden on operators of critical monitoring services such as maritime and air traffic control. In these fields, vessels and aircraft have sensors that transmit data to a control center. Because of the large volume of collected data, it is infeasible for monitoring stations to display all of the information on monitoring screens that have limited sizes. This paper proposes a method for automatically selecting maritime traffic stream data for display from a large number of candidates in a context-aware manner. Safety is the most important concern in maritime traffic control, and special care must be taken to avoid collisions between vessels at sea. It presents an architecture for an adaptive information visualization system for a maritime traffic control service. The proposed system adaptively determines the information to be displayed based on the safety evaluation scores and expertise of vessel traffic service operators. It also introduces a method for safety context acquisition to assess the risk of collisions between vessels, using parallel and distributed processing of maritime stream data transmitted by sensors on the vessels at sea. It provides an information-filtering, knowledge extraction method based on the work logs of traffic service operators, using a machine learning technique to generate a decision tree. We applied the proposed system architecture to a large dataset collected at a port. Our results indicate that the proposed system can adaptively select traffic information according to port conditions and to ensure safety and efficiency.

关键词： big data stream data context-aware service distributed and parallel processing vessel traffic service maritime traffic stream sensor data

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Extending X3D for distributed multimedia processing and control 09

Extending X3D for distributed multimedia processing and cont...

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Proceedings of the 14th International Conference on 3D Web Technology

作者： Michael Repplinger Alexander Löffler Benjamin Schug Philipp Slusallek Saarland University

ISBN: (纸本)9781605584324

Web-based applications of interactive 3D computer graphics are showing a tendency to get more interconnected and visually complex. Virtual communities like Second Life demand realism not only in terms of realistic rendering, but also in terms of integrated multimedia content. For these Web-based applications, X3D is the ISO-standard way to specify and manipulate scene descriptions. In terms of multimedia integration, however, X3D offers to specify content only in the form of URLs pointing to files. Modern middleware for distributed multimedia, on the other hand, allows applications to harness the full range of multimedia processing as well as transparent use and full control of both local and remote components. Integrating a full multimedia processing pipeline into X3D would enable Web authors to use, for example, streaming media, post-processing on media streams, or routing between scene elements (e.g., sensors) and elements of multimedia processing (e.g., TV cards). A full integration of multimedia in X3D is yet *** this paper, we propose X3D extensions for a seamless mapping of a distributed multimedia flow graph onto an X3D scene graph, making all the features of a distributed multimedia middleware accessible and usable within an X3D scene. We present our proposed specification and implementation of multimedia nodes for X3D. Using examples and implemented X3D application scenarios, we show the simplicity and feasibility of our approach.

关键词： X3D multimedia middleware distributed processing distributed flow graph distributed and parallel processing

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A Software Architect Based on Grid Computing for Accelerating Simulation Speed

A Software Architect Based on Grid Computing for Acceleratin...

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11th International Conference on Electrical Machines and Systems

作者： Michael Zhou

As power system are pushed to their limits and have become more complicated,software tools and simulations have played a more important role,which means that the operation and control of power system is actually becoming a huge data-intensive,information-intensive, computationally-intensive *** systems rely much more on faster computing tools and methods,In order to faster the calculation and simulation speed,a distributed and parallel power system grid computing platform,which is based on certain internet open sources and formed by integrating Gridgain,a platform that"gridfy"the process with high efficiency,into InterPSS,a power system simulation platform,is *** platform,named InterPSS Grid Computing Platform,works by gathering the unused computer hardware resources in the local area network(LAN),and splitting a task into certain sub-tasks, and sending them to the available computing resources to perform computing independently,and sending back the sub-results to the master *** study cases,load flow and transient stability calculation under N-1 shows the high performance of the proposed solution.

关键词： power system distributed and parallel processing Grid Computing power system simulation open source software

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