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检索条件"任意字段=8th International Conference on Parallel and Distributed Computing, Applications and Technologies"

共 1804 条记录，以下是681-690 订阅

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Operator Placement for Efficient distributed Complex Event Processing in MANETs 11

Operator Placement for Efficient Distributed Complex Event P...

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11th IEEE international conference on Wireless and Mobile computing, Networking and Communications (WiMob)

作者： Starks, Fabrice Plagemann, thomas Peter Univ Oslo Dept Informat Oslo Norway

ISBN: (纸本)9781467377010

Complex Event Processing (CEP) and Mobile Adhoc networks (MANETs) are two technologies that can be used to enable monitoring applications for Emergency and Rescue missions (ER). MANETs are characterized by energy limitations, and in-network processing or distributed CEP is one possible solution. Operator placement mechanism for distributed CEP has a direct impact on energy consumption. Existing operator placement mechanisms focus on static network topologies and are therefore inappropriate for MANETs scenarios. We propose a novel energy efficient decentralized distributed placement mechanism, designed to achieve fast convergence with minimal data transmission cost while achieving a near optimal placement assignment. We compare our decentralized placement mechanism with a centralized approach under different mobility scenarios. Furthermore, we evaluate the distributed CEP under different workload scenarios in order to gain additional insight into different performance characteristics of the system. Finally, we measure the impact of a simple placement replication scheme on the overall system performance in terms of delay and message overhead. Our decentralized placement mechanism achieves up to almost 50% lower message overhead compared to the centralized approach, and it has lower message overhead across different mobility scenarios compared to the centralized approach. the placement replication scheme achieves up to 51% lower delay compared to the decentralized placement mechanism with no replication.

关键词： Computer networks Mobile computing parallel and distributed computing Performance Wireless communications

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Performance Enhancement of distributed K-Means Clustering for Big Data Analytics through In-memory Computation 8

Performance Enhancement of Distributed K-Means Clustering fo...

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8th international conference on Contemporary computing (IC3)

作者： Ketu, Shwet Agarwal, Sonali Indian Inst Informat Technol Allahabad Uttar Pradesh India

ISBN: (纸本)9781467379489

Big Data analytics are recently coming up as prominent research area in the field of Information Technology serving various data driven domains for effective processing of big data. Big data analytics have been facing various challenges such as inefficient storage, processing delays, low rate of information retrieval, complex algorithms which cannot be handled and managed using traditional methods. For assisting software developers to deal with big data challenges, new programming frameworks are required. In this research paper Hadoop MapReduce and Apache Spark are taken for this purpose which supports on-disk and in-memory computation respectively. Clustering is one of the important tasks of big data mining used for information retrieval and knowledge discovery. In this research work, we are analyzing the performance of distributed K-Means clustering based on in-memory and on-disk computational models. For performance enhancement of distributed K-Means clustering, in-memory and on-disk computational models have been adopted and an experimental analysis has been performed.

关键词： Big data Big data analytic distributed K-Mean Hadoop MapReduce Apche Spark On- disk computation In-memory computation

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Unified distributed computing and Co-ordination in Pervasive/Ubiquitous Networks with Mobile Multi-Agent Systems using a Modular and Portable Agent Code Processing Platform 6

Unified Distributed Computing and Co-ordination in Pervasive...

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6th international conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN) / 5th international conference on Current and Future Trends of Information and Communication technologies in Healthcare (ICth)

作者： Bosse, Stefan Univ Bremen Dept Math & Comp Sci D-28359 Bremen Germany

A novel and unified approach for reliable distributed and parallel computing using mobile agents is introduced. the agents can be deployed in large scale and hierarchical network environments crossing barriers transparently. the networks can consist of high- and low-resource nodes ranging from generic computers to microchips, and the supported network classes range from body area networks to the Internet including any kind of sensor and ambient network. Agents are represented by mobile program code that can be modified at run-time. the presented approach enables the development of sensor clouds and smart systems of the future integrated in daily use computing environments and the Internet. Agents can migrate between different hardware and software platforms by migrating the program code of the agent, embedding the state and the data of an agent, too. the entire information exchange and coordination of agents with other agents and the environment is performed by using a tuple space database. Beside architecture specific hardware and software implementations of the agent processing platform, there is a JavaScript (JS) implementation layered on the top of a distributed management layer. the JS platform enables the integration of Multi-agent Systems (MAS) in Internet server and application environments (e. g., WEB browser). Agents can migrate transparently between hardware-level sensor networks and WEB browser applications or network servers and vice versa without any transformation required. (C) 2015 the Authors. Published by Elsevier B.V.

关键词： Sensor Networks Cloud computing Mobile Agents Heterogeneous Networks Embedded Systems Agent Processing Platform

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Two Class Fisher's Linear Discriminant Analysis Using MapReduce 17

Two Class Fisher's Linear Discriminant Analysis Using MapRed...

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17th IEEE UKSim-AMSS international conference on Computer Modelling and Simulation (UKSim)

作者： Anchalia, Prajesh P. Roy, Kaushik Roy, Kunal RV Coll Engn Dept CSE Bangalore Karnataka India Global Acad Technol Dept CSE Bangalore Karnataka India

ISBN: (纸本)9781479987122

Information explosion propelled by the exponential growth in digitised data is an unstoppable reality. To be able to extract relevant and useful knowledge from this voluminous data in order to make well-informed decision is a competitive advantage in the information age. However, the attempts to transform raw data into valuable knowledge face both data and computational intensive challenges. As a result, parallel and distributed computing is often strongly sought after to alleviate these challenges. While there are many distributed computing technologies being proposed over the years, MapReduce has gained an immense amount of interest in recent years due to its simplicity and superb scalability at low cost. In this paper we implement the fisher linear discriminant technique to reduce dimensionality and remove the so-called "noisy" data values from a given data set and project the data values in the direction of largest variance. Few of Fisher linear discriminant analysis' applications are Life Sciences, Face Recognition, Music and Speech classification. We implement the Fisher Linear Discriminant on a distributed computing environment and we conclude that it outperforms the sequential implementation.

关键词： MapReduce Fisher's Linear Discriminant Data Mining Hadoop distributed computing

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parallel and distributed computing, applications and technologies, PDCAT Proceedings

Parallel and Distributed Computing, Applications and Technol...

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15th international conference on parallel and distributed computing, applications and technologies, PDCAT 2014

ISBN: (纸本)9781479983346

the proceedings contain 30 papers. the topics discussed include: benchmarking and analysis of variations of work stealing scheduler on clustered system;conflict-free code block scheduling to hide SpMT inter-core register sync delay;dealing with skewed data in structured overlays using variable hash functions;distributive interoperable executive library (DIEL) for systems of multiphysics simulation;on the shallow-light Steiner tree problem;fast ICA on modern GPU architectures;fault-tolerant routing based on improved safety levels in pancake graphs;improve LLC bypassing performance by memory controller improvements in heterogeneous multicore system;comparison of binding approaches of scheduled multiphase application onto linear multicore architecture;Using rCUDA to reduce GPU resource-assignment fragmentation caused by job scheduler;practical anonymization for protecting privacy in combinatorial maps;and prediction of spatial and temporal data: a web tool based on georeferenced resources.

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Is there a Free Lunch for Image Feature Extraction in Web applications 8th

Is There a Free Lunch for Image Feature Extraction in Web Ap...

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8th international conference on Similarity Search and applications (SISAP)

作者： Krulis, Martin Charles Univ Prague Fac Math & Phys Parallel Architectures Algorithms Applicat Res Gr Malostranske Nam 25 Prague Czech Republic

ISBN: (纸本)9783319250878;9783319250861

Feature extraction is one of the essential parts of multimedia indexing in similarity search and content-based retrieval methods. Most applications that employ these methods also implement their client side interface using web technologies. the world wide web has become a well-established platform for distributed software and virtually all personal computers, tablets, and smartphones are equipped with a web browser. In the past, most applications employed a strict client-server approach, where the client part (running in the browser) handles only the user interface and the server side handles data storage and business logic. However, the client-side technologies leaped forward with the new HTML5 standard and the web browser has become capable of handling much more complex tasks. In this paper, we propose a model where the multimedia indexing is handled at the client side, which reduces necessary computational power of the server to run a web application that manages large multimedia database. We have implemented an in-browser image feature extractor and compared its performance with a server implementation.

关键词： HTML5 Image Feature extraction Multimedia indexing

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Scalable and parallel Machine Learning Algorithms for Statistical Data Mining - Practice & Experience 38

Scalable and Parallel Machine Learning Algorithms for Statis...

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38th international Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)

作者： Riedel, M. Goetz, M. Richerzhagen, M. Glock, P. Bodenstein, C. Memon, A. S. Memon, M. S. Forschungszentrum Julich Juelich Supercomp Ctr Julich Germany Univ Iceland Sch Nat Sci & Engn Reykjavik Iceland

ISBN: (纸本)9789532330854

Many scientific datasets (e. g. earth sciences, medical sciences, etc.) increase with respect to their volume or in terms of their dimensions due to the ever increasing quality of measurement devices. this contribution will specifically focus on how these datasets can take advantage of new 'big data' technologies and frameworks that often are based on parallelization methods. Lessons learned with medical and earth science data applications that require parallel clustering and classification techniques such as support vector machines (SVMs) and density-based spatial clustering of applications with noise (DBSCAN) are a substantial part of the contribution. In addition, selected experiences of related 'big data' approaches and concrete mining techniques (e. g. dimensionality reduction, feature selection, and extraction methods) will be addressed too. In order to overcome identified challenges, we outline an architecture framework design that we implement with open available tools in order to enable scalable and parallel machine learning applications in distributed systems.

关键词： Scalability Earth sciences Machine learning algorithms big data Dataset mining Representation of data Statistical Data parallel Lines distributed Systems Support Vector Network data mining

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8th ACM international conference on PErvasive technologies Related to Assistive Environments, PETRA 2015 - Proceedings

8th ACM International Conference on PErvasive Technologies R...

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8th ACM international conference on PErvasive technologies Related to Assistive Environments, PETRA 2015

ISBN: (纸本)9781450334525

the proceedings contain 100 papers. the topics discussed include: comparing projected in-situ feedback at the manual assembly workplace with impaired workers;maintaining good relationships in clinical setting: the bonus DOMUS project;pot hunter: a virtual reality game for analyzing range of motion;a survey on an ingestible sensor for evaluating medication adherence in elderly people;an interactive framework for learning user-object associations through human-robot interaction;automatic soundscape quality estimation using audio analysis;nonverbal communication with a humanoid robot via head gestures;assistive positioning system based inertial techniques and wavelet denoising;an intra-fraction markerless daily lung tumor localization algorithm for EPID images;a framework for self-managing database support and parallel computing for assistive systems;a prototype of a real-time solution on mobile devices for heart tele-auscultation;and sole based tactile information display for visually impaired pedestrian navigation.

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Context-Aware Provisioning and Management of Cloud applications

Context-Aware Provisioning and Management of Cloud Applicati...

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4th international conference on Cloud computing and Services Sciences (CLOSER)

作者： Breitenbuecher, Uwe Binz, Tobias Kopp, Oliver Leymann, Frank Wieland, Matthias Univ Stuttgart Inst Architecture Applicat Syst D-70174 Stuttgart Germany Univ Stuttgart Inst Parallel & Distributed Syst D-70174 Stuttgart Germany

ISBN: (纸本)9783319254142;9783319254135

the automation of application provisioning and management is one of the most important issues in Cloud computing. However, the steadily increasing number of different services and software components employed in composite Cloud applications leads to a high risk of unintended side effects when different technologies work together that bring their own proprietary management APIs. Due to unknown dependencies and the increasing diversity and heterogeneity of employed technologies, even small management tasks on a single component may compromise the whole application functionality for reasons that are neither expected nor obvious to non-experts. In this paper, we tackle these issues by introducing a method that enables detecting and correcting unintended effects of provisioning and management tasks in advance by analyzing the context in which the tasks are executed. We validate the method practically and show how context-aware expert management knowledge can be applied fully automatically to provision and manage running Cloud applications.

关键词： Application management Provisioning Context Automation Cloud computing

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Hierarchical Topology in parallel Differential Evolution 8

Hierarchical Topology in Parallel Differential Evolution

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8th international conference on Numerical Methods and applications (NMA)

作者： Bujok, Petr Univ Ostrava Dept Informat & Comp Fac Comp Sci Ostrava 70103 Czech Republic

ISBN: (纸本)9783319155845;9783319155852

A new differential evolution (DE) algorithm with a parallel hierarchical topology (HDE) is proposed. the main goal of the paper is to study how the performance of the algorithm is influenced by the use of parallel migration model. the hierarchical model has several control parameters and the influence of these parameters setting is also studied. the performance of HDE algorithm is compared with non-parallel DE algorithm on CEC2013 benchmark suite. Experimental results show that the HDE outperforms the non-parallel DE algorithm significantly in 27 out of 28 test problems.

关键词： Differential evolution parallel model Hierarchical topology CEC2013 benchmark suite

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