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检索条件"任意字段=10th International Conference on Parallel and Distributed Computing, Applications and Technologies"

共 1767 条记录，以下是661-670 订阅

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distributed Evolutionary computing Migration Strategy by Incident Node Participation 10th

Distributed Evolutionary Computing Migration Strategy by Inc...

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10th international conference on Large-Scale Scientific Computations (LSSC)

作者： Balabanov, Todor Zankinski, Iliyan Barova, Maria Bulgarian Acad Sci Inst Informat & Commun Technol Acad G Bonchev StrBlock 2 BU-1113 Sofia Bulgaria

ISBN: (纸本)9783319265209;9783319265193

distributed evolutionary algorithms are implemented on heterogeneous computing nodes. In a distributed environment it is usual these nodes to differ in operating system and hardware. Such an environment has major problems related to network latency. Some of the evolutionary optimization algorithms are very suitable for distributed computing implementation, because of their high level of parallel scalability. In most cases only fitness function calculation is distributed synchronously (or asynchronously). In this case the population is presented only in the master node. In the next case each separate node has part of the distributed population (it is called island model). the last common model is based on shared memory and each computing node has access to the whole population (it is called fine-grained model). All other models are some hybridization. In the island model there is a common parameter related to migration strategy. the most often used node topology is the ring topology. On a regular basis each node sends its best individual to the next node in the ring. In this paper, a hybrid model, based on incident node participation in star topology, is proposed.

关键词： distributed computing Evolutionary algorithms Migration strategies

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10th international Symposium on Algorithms and Experiments for Sensor Systems, Wireless Networks and distributed Robotics, ALGOSENSORS 2014

10th International Symposium on Algorithms and Experiments f...

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10th international Symposium on Algorithms and Experiments for Sensor Systems, Wireless Networks and distributed Robotics, ALGOSENSORS 2014

ISBN: (纸本)9783662460177

the proceedings contain 13 papers. the special focus in this conference is on Robot Planning, Data Structures on Graphs and Wireless Networks. the topics include: Multi robot foremost coverage of time-varying graphs;strategies for parallel unaware cleaners;minimum-traveled-distance gathering of oblivious robots over given meeting points;computing the dynamic diameter of non-deterministic dynamic networks is hard;improved spanners in networks with symmetric directional antennas and minimum latency aggregation scheduling in wireless sensor networks.

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A workflow runtime environment for manycore parallel architectures 10

A workflow runtime environment for manycore parallel archite...

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10th Workshop on Workflows in Support of Large-Scale Science, WORKS 2015

作者： Janetschek, Matthias Prodan, Radu Benedict, Shajulin Institute for Computer Science University of Innsbruck Austria

ISBN: (纸本)9781450339896

We introduce a new Manycore Workflow Runtime Environment (MWRE) to efficiently enact traditional scientific workflows on modern manycore computing architectures. In contrast to existing engines that enact workflows acting as external services, MWRE is compiler-based and translates workflows specified in the XMLbased InteroperableWorkflow Intermediate Representation (IWIR) into an equivalent C++-based program. this program efficiently enacts the workflow as a stand-alone executable by means of a new callback mechanism that resolves dependencies, transfers data, and handles composite activities. Experimental results on a number of real-world workflows demonstrate that MWRE clearly outperforms existing Java-based workflow engines designed for distributed (Grid/Cloud) computing infrastructures in terms of enactment time, is generally better than an existing script-based engine for manycore architectures (Swift), and sometimes gets even close to an artificial baseline implementation of the workflows in the standard OpenMP language for shared memory systems. © 2015 ACM.

关键词： Engines

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Collaborative learning in an artifact ecology: A distributed cognition perception 15

Collaborative learning in an artifact ecology: A distributed...

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10th ACM international conference on Interactive Tabletops and Surfaces, ITS 2015

作者： Vasiliou, Christina Cyprus Interaction Lab Cyprus University of Technology 30 Archbishop Kyprianou Str. Limabol3036 Cyprus

ISBN: (纸本)9781450338998

this work aims to extend our understanding of how groups of learners collaborate in a learning environment rich in technologies, namely an artifact ecology. For the purpose of this investigation we enriched a postgraduate HCI course with four identical technology rich settings that aimed to support student collaborative activities around a design problem. Following an ethnographic approach, we collected qualitative data from an HCI course over three years resulting in a rich dataset for analysis. Initial studies helped us understand the domain knowledge, context, and learners' needs and experiences. then, using distributed Cognition (DC) framework we worked toward understanding the interdependencies of learners, tasks, and technologies in the environment and highlighting aspects of redesign. the findings of these individual studies were then combined in order to provide a holistic understanding of the collaborative activities in an artifact ecology. © Copyright 2015 by the Abociation for computing Machinery, Inc. (ACM).

关键词： Curricula

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Heuristic Algorithms for Optimizing Array Operations in parallel PGAS-programs 13th

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13th international conference on parallel computing technologies (PaCT)

作者： Kulagin, Ivan Paznikov, Alexey Kurnosov, Mikhail Siberian State Univ Telecommun & Informat Sci Novosibirsk 630102 Russia RAS Siberian Branch Rzhanov Inst Semicond Phys Novosibirsk 630090 Russia St Petersburg Elect Univ LETI St Petersburg 197376 Russia

the algorithms for optimizing array operations in PGAS-programs are represented. they minimize execution time by taking into account hierarchical structure of computer systems in reduction and by preloading of remote ... 详细信息

ISBN: (纸本)9783319219097;9783319219080

关键词： PGAS Compiler optimization Reduction Scalar replacement

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QoS-Aware and Fair Resource Allocation with Carrier Aggregation in LTE-A Networks

QoS-Aware and Fair Resource Allocation with Carrier Aggregat...

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international conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Peisheng Yan Xin Chen Zhuo Li Yudong Jia School of Computer Science Beijing Information Science & Technology University Beijing P. R. China Beijing Key Laboratory of Internet Culture and Digital Dissemination Research Beijing Information Science & Technology University Beijing P. R. China Cloud Technical Architecture Department Dawing Cloud Computing Technologies Limited Company Beijing P. R. China

ISBN: (纸本)9781509056972

With the rapid growth of bandwidth-intensive applications, Carrier Aggregation (CA) has been introduced in Long Term Evolution-Advanced (LTE-A) Networks to provide higher data rates. In this paper, we investigate the joint resource block allocation and link adaptation problem with CA in LTE-A downlink. the problem is formulated as an Integer Programming problem aimed at maximizing the cell throughtput while guaranteeing Quality of Service (QoS) of each User Equipment (UE), in the form of the minimum transmission rate. We also consider the proportional fairness of radio allocation among UEs. Due to the NP-hardness of the problem, we propose an efficient algorithm QA-PFRA. QA-PFRA consists of two phases. In the first one we assign radio resource to UEs successively for QoS requirements according to UEs' priority, and in the second one we assign CCs to other UEs to maximize the cell weighted throughput. We develop a simulator to evaluate the performance of QA-PFRA. For comparison, we also implement GA algorithm and ERAA algorithm. It is found that the cell throughput obtained by QA-PFRA is about 70 higher than that obtained by ERAA, and QA-PFRA can also achieve higher throughput compared with GA when the UEs are sparsely distributed in the cell. Furthermore, we can observe that Jain's fairness index obtained by QA-PFRA is about 10 higher than that obtained by GA and 40 higher than that obtained by ERAA.

关键词： Quality of service Resource management throughput Signal to noise ratio Interference Mobile communication Downlink

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A distributed Ensemble Scheme for Nonlinear Support Vector Machine 10

A Distributed Ensemble Scheme for Nonlinear Support Vector M...

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IEEE 10th international conference on Intelligent Sensors Sensor Networks & Information Proc (IISSNIP)

作者： Lai, Wei-Chih Huang, Po-Han Lee, Yuh-Jye Chiang, Alvin Natl Taiwan Univ Sci & Technol Taipei Taiwan

ISBN: (纸本)9781479980550

We propose an ensemble scheme with a parallel computational structure which we call distributed Ensemble Support Vector Machine (DESVM) to overcome the difficulties of large scale nonlinear Support Vector Machines (SVMs) in practice. the dataset is split into many stratified partitions. Each partition might be still too large to be solved by using conventional SVM solvers. We apply the reduced kernel trick to generate a nonlinear SVM classifier for each partition that can be treated as an approximation model based on the partial dataset. then, we use a linear SVM classifier to fuse the nonlinear SVM classifiers that are generated from all data partitions. In this linear SVM training model, we treat each nonlinear SVM classifier as an "attribute" or an "expert". In the ensemble phase, DESVM generates a fusion model which is a weighted combination of the nonlinear SVM classifiers. It can be explained as a weighted voting decision made by a group of experts. We test our proposed method on five benchmark datasets. the numerical results show that DESVM is competitive in accuracy and has a high speed-up. thus, DESVM can be a powerful tool for binary classification problems with large scale not linearly separable datasets.

关键词： distributed computing ensemble learning parallel algorithm reduced kernel trick support vector machine

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Large Scale distributed Localization Based on RSS and Mass-Spring Model

Large Scale Distributed Localization Based on RSS and Mass-S...

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international conference on P2P, parallel, Grid, Cloud and Internet computing (3PGCIC)

作者： Bart Praats Rafael Berkvens Glenn Ergeerts Maarten Weyn MOSAIC FTI University of Antwerp Antwerp Belgium

ISBN: (纸本)9781467394741

Large scale localization has gained interest in the last few years together with wireless sensor networks. applications such as a swarm of drones or a sensor network to control an environment already exist but do not cover scales up to thousands of nodes. In this paper, a method for large scale distributed localization is developed based on existing technologies including received signal strength and mass-spring model (MSM). First, we created a theoretical model based on specific indoor and outdoor tests. Based on this model, a scaled up simulation was done using an MSM-based algorithm. Using this simulation, an average error of up to 7.66 m could be achieved in a field of 100 m by 100 m.

关键词： Databases Computational modeling Wireless sensor networks Radio frequency Receiving antennas Wrist

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A distributed Graph Based Approach for Rough Classifications Considering Dominance Relations Between Overlapping Classes 10

A Distributed Graph Based Approach for Rough Classifications...

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10th international conference on Intelligent Systems - theories and applications (SITA)

作者： Laghmari, K. Ramdani, M. Marsala, C. Univ Hassan II Casablanca FSTM Lab Informat Mohammedia BP 146 Mohammadia 20650 Morocco Univ Paris 06 Univ Sorbonne CNRS LIP6UMR 7606 F-75005 Paris France

ISBN: (纸本)9781509002207

Several data from real world applications involves overlapping classes. Data is allowed to belong to multiple classes with different membership degrees. In this paper, we explore a different concept characterizing social networks, documents, and most of biological and chemical datasets: data could have multiple classes, but dominant classes are better noticed than dominated classes. For example, a document could discuss economy and politics, but it would be more focused on politics. A molecule could have multiple odors, but experts could notice some odors better than others. We are interested in this type of data, where a dominance relation exists between classes. Experts could easily make mistakes because dominated classes are hardly noticed. Data incoherence is a serious problem but not the only one. there is too much irrelevant and redundant attributes. Unfortunately this increases the computational time of generating classifiers. Our first challenge is to find an adapted model to overlapping classes considering dominance relations. the second challenge is to find the most relevant attributes. Finally the third challenge is to ensure that the approach gives results in an acceptable time. We address those challenges by taking advantage of the rough set theory, which is suited for incoherent data and allows multiple classes and attributes selection. the proposed approach works in a parallel and decentralized way to reduce the computational time. We tested it on real chemical data and the collected results are very promising.

关键词： Approximation methods Chlorine Databases Decision trees Servers Symmetric matrices Training Symmetric matrix Approximation method Servers Decision Trees Chlorine Database Functional training computational time Politics Classes

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MR-SPS: Scalable parallel Scheduler for YARN/MapReduce Platform 10

MR-SPS: Scalable Parallel Scheduler for YARN/MapReduce Platf...

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IEEE 10 Int Conf on Service Operations and Logistics and Informatics(SOLI)

作者： Mennour, Rostom Batouche, Mohamed Hannache, Oussama Abdelhamid Mehri Constantine 2 Univ Fac NTIC MISC Lab Constantine Algeria Abdelhamid Mehri Constantine 2 Univ Fac NTIC Dept Comp Sci Constantine Algeria

ISBN: (纸本)9781467384803

In the Big Data era, MapReduce has been the most utilized model in academia and industry. the main objective of MapReduce and its well-known implementation Hadoop is to run distributed applications to analyze huge amount of datasets, on very large clusters of commodity machines. this can be very time consuming. Also, the cluster that runs MapReduce applications has to be very scalable. In order to improve the performance of the MapReduce model, efficient scheduling algorithms have to be developed. Now day, Scalability is a major concern for applications that works on datasets measured by petabytes. Schedulers for such applications must allow a high scalability and an optimal utilization of resources in order to minimize the execution time. For this end we propose MR-SPS, a scalable parallel scheduling algorithm that takes care of scalability of the cluster and its performance by managing workload and data locality. Our scheduler works in a parallel manner, which allows a higher use of the capacities that the Resource-manager can eventually provide, this will increase the number of node that it can manage. For experiments, we have used CloudSim to simulate MR-SPS and other scheduling algorithms designed for MapReduce model. the results show the superiority of our implementation.

关键词： Big Data Processing Scheduling MapReduce YARN parallel Processing Performance Scalability

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