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检索条件"任意字段=9th International Conference on Parallel and Distributed Computing, Applications and Technologies"

共 1772 条记录，以下是591-600 订阅

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Massively parallel technologies Based on Microelectromechanical Systems for Improving Effective Functioning of the Aircraft 4

Massively Parallel Technologies Based on Microelectromechani...

引用

4th IEEE international conference Methods and Systems of Navigation and Motion Control (MSNMC)

作者： Serhii, Tovkach Natl Aviat Univ Kiev Ukraine

ISBN: (纸本)9781509010530

the problem of development adaptive control systems based on microelectromechanical systems for reduce turbulent flow of the aircraft has been considered. Complex solution based on microelectromechanical systems and graphic processing platform NVIDIA Tegra, which includes massively parallel technology, has been proposed. It develops parallel processing software based on algorithms that delivers scaling and speed up on distributed memory systems for high performance applications. the distributed microelectromechanical systems technique involves spreading integrated sense-compute-act modules over areas to sense the physical world and act upon it. Tiny elements can reduce drag by sensing vortices and interacting with them. It will help to reach better maneuverability, increase the range of aircraft payload and capability.

关键词： turbulent flow control microelectromechanical sysytems (MEMS) parallel computing scaling graphic processing unit

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LAST-HDFS: Location-Aware Storage Technique for Hadoop distributed File System 9

LAST-HDFS: Location-Aware Storage Technique for Hadoop Distr...

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9th IEEE international conference on Cloud computing (CLOUD)

作者： Liao, Cong Squicciarini, Anna Lin, Dan Penn State Univ Coll Informat Sci & Technol University Pk PA 16802 USA Missouri Univ Sci & Technol Dept Comp Sci Rolla MO USA

ISBN: (纸本)9781509026197

Enabled by the state-of-the-art cloud computing technologies, cloud storage has gained increasing popularity in recent years. Despite of the benefit of flexible and reliable data access offered by such services, users have to bear with the fact of not actually knowing the whereabouts of their data. the lack of knowledge and control of the physical locations of data could raise legal and regulatory issues, especially for certain sensitive data that are governed by laws to remain within certain geographic boundaries and borders. In this paper, we study the problem of data placement control within distributed file systems supporting cloud storage. Particularly, we consider the open source Hadoop file system (HDFS) as the underlying architecture, and propose a location-aware cloud storage system, named LAST-HDFS, to support and enforce location-aware storage in HDFS-based clusters. In addition, it also includes a monitoring system deployed at individual hosts to oversee and detect potential data placement violations due to the existence of malicious datanodes. We carried out an extensive experimental evaluation in a real cloud environment that demonstrates the effectiveness and efficiency of our proposed system.

关键词： Location-Awareness MapReduce HDFS

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parallel Gathering Discovery over Big Trajectory Data 4

Parallel Gathering Discovery over Big Trajectory Data

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4th IEEE international conference on Big Data (Big Data)

作者： Xian, Yongyi Liu, Yan Xu, Chuanfei Concordia Univ Fac Engn & Comp Sci Montreal PQ Canada

ISBN: (纸本)9781467390057

the advances in location-acquisition technologies have generated massive spatio-temporal trajectory data, which represent the mobility of a diversity of moving objects over time, such as people, vehicles, and animals. Discovery of traveling companions on trajectory data has many real-world applications. Most of existing discovery approaches are limited to centralized computing, while these techniques for handling large-scale trajectory data require considerable performance improvement. parallel computing essentially provides an alternative method for handling this problem. In this work, we first present the design and implementation of both batch and streaming gathering patterns discovery algorithm in a distributed parallel computing fashion. Afterwards, we further propose several optimization techniques for efficient computation. Finally we conduct extensive experiments based on a public dataset to evaluate the efficiency of our approaches and effectiveness of optimizations using Amazon EC2 clusters.

关键词： parallel computing gathering discovery trajectory data

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distributed RDFS Rules Reasoning for Large-Scaled RDF Graphs Using Spark 9

Distributed RDFS Rules Reasoning for Large-Scaled RDF Graphs...

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9th international conference on Service Science, ICSS 2016

作者： Li, Ren Zhang, Qi Wang, Huibin Wang, Guiping College of Information Science and Engineering Chongqing Jiaotong University Chongqing China

ISBN: (纸本)9781509027279

Scalable processing on large-scaled RDF graphs becomes a critical issue with the explosion of semantic web technologies. Most of the existing distributed RDF querying and reasoning solutions are designed based on the MapReduce paradigm. However, MapReduce should be further optimized since several inherent limitations such as lack of efficient job scheduling and iterative computing mechanisms affect its performance and flexibility. To overcome the drawbacks, some novel distributed programming models like Spark have been released and comprehensively used. To further improve the efficiency of RDFS rules reasoning for large-scaled RDF data, this paper design a graph-based RDF data partitioning and storage schema based on HBase. A novel RDFS reasoning approach is proposed by exploiting the Spark context. An experiment on the standard LUBM benchmark shows that our approach is more efficiency than existing solution. © 2016 IEEE.

关键词： Digital storage

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Agent and Multi-Agent Systems: technologies and applications 9th KES international conference, KES-AMSTA 2015 Sorrento, Italy, June 2015, Proceedings

引用

2016年

作者： Gordan Ježić Robert J Howlett Lakhmi C Jain

ISBN: (纸本)9783319386416

Agents and multi-agent systems are related to a modern software paradigm which has long beenrecognized as a promising technology for constructingautonomous, complex andintelligent systems. thetopics covered in this volume include agent-oriented software engineering, agent co-operation, co-ordination, negotiation, organization and communication, distributed problem solving, specification of agentcommunication languages, agentprivacy, safety and security, formalization of ontologies and conversational agents. the volume highlights new trends andchallenges in agent and multi-agent research and includes 38 papers classifiedin the following specific topics:learningparadigms, agent-based modeling and simulation, business model innovation anddisruptive technologies, anthropic-oriented computing, serious games andbusiness intelligence, design and implementation of intelligent agentsand multi-agent systems, digital economy, and advances in networkedvirtual enterprises. Published papershave been presented at the 9th KES conference on Agent and Multi-Agent Systems technologies and applications(KES-AMSTA 2015) held in Sorrento, Italy. Presented results should be of value tothe research community working in the fields of artificial intelligence, collective computational intelligence, robotics, dialogue systems and, inparticular, agent and multi-agent systems, technologies, tools and applications.

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Learning to diagnose stragglers in distributed computing 9

Learning to diagnose stragglers in distributed computing

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9th Workshop on Many-Task computing on Clouds, Grids, and Supercomputers, MTAGS 2016

作者： Li, Cong Shen, Huanxing Huang, Tai Intel Corporation No. 880 Zixing Road Shanghai China

ISBN: (纸本)9781509052127

In cloud computing and high performance computing, a large job is typically divided into many small tasks for parallel execution in a distributed environment. Due to different reasons, some tasks (so-called 'stragglers') are considerably slower than the others, delaying the completion of the job. We propose a new machine learning approach to automatically identify and diagnose the stragglers. To first identify stragglers, an unsupervised clustering method is employed to group the tasks based on their execution time. We then use a supervised rule learning algorithm to learn diagnosis rules inferring the stragglers with their resource assignment and performance counter data. Preliminary experiments from the trace of a Google's Borg cluster demonstrate that our method is able to generate simple and easy-to-read rules with decent performance in predicting stragglers. © 2016 IEEE.

关键词： distributed computer systems

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An Improved Model for Live Migration in Data Centre Simulators 16

An Improved Model for Live Migration in Data Centre Simulato...

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9th IEEE/ACM international conference on Utility and Cloud computing (UCC)

作者： De Maio, Vincenzo Kecskemeti, Gabor Prodan, Radu Univ Innsbruck Inst Comp Sci Technikerstr 21A A-6020 Innsbruck Austria MTA SZTAKI Lab Parallel & Distributed Syst Victor Hugo U 18-22 H-1132 Budapest Hungary

Due to the difficulty of employing real data centres9; infrastructure for assessing the effectiveness of energy-aware algorithms, many researchers resort to use simulation tools. these tools require precise and det... 详细信息

ISBN: (纸本)9781450346160

Due to the difficulty of employing real data centres' infrastructure for assessing the effectiveness of energy-aware algorithms, many researchers resort to use simulation tools. these tools require precise and detailed models for virtualized data centres in order to deliver accurate results. In recent years, many models have been proposed, but most of them either do not consider energy consumption related to virtual machine (VM) migration or do not investigate some of the energy impacting components (e.g. CPU, network, storage). We propose a new model for data centre energy consumption that takes into account the previously omitted components and provides more accurate energy consumption predictions compared to other state-of-the- art solutions. We evaluate our model's accuracy in a comprehensive set of scenarios implemented in the combined GroudSim/DISSECT-CF simulator. Our analysis revealed a significant improvement in accuracy (up to 42.5%) in the modelled energy consumption compared to a similar state-of- the-art simulator.

关键词： Energy consumption Data models Computational modeling Load modeling Cloud computing Bandwidth Atmospheric modeling

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Improving Coding Performance and Energy Efficiency of Erasure Coding Process for Storage Systems - A parallel and Scalable Approach 9

Improving Coding Performance and Energy Efficiency of Erasur...

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9th IEEE international conference on Cloud computing (CLOUD)

作者： Chen, Hsing-bung Fu, Song Los Alamos Natl Lab HPC Grp 5 Los Alamos NM 87545 USA Univ North Texas Dept Comp Sci & Engn Denton TX 76203 USA

ISBN: (纸本)9781509026197

Erasure code based object storage systems are becoming popular choices for archive storage systems due to cost-effective storage space saving schemes and higher fault-resilience capabilities. Both erasure code encoding and decoding procedures involve heavy array, matrix, and table-lookup compute intensive operations. With today's advanced CPU design technologies such as multi-core, many-core, and streaming SIMD instruction sets we can effectively and efficiently adapt the erasure code technology in cloud storage systems and apply it to handle very large-scale date sets. Current solutions of the erasure coding process are based on single process approach which is not capable of processing very large data sets efficient and effectively. To prevent the bottleneck of a single process erasure encoding process, we utilize the task parallelism property from a multicore computing system and improve erasure coding process with parallel processing capability. We have leveraged open source erasure coding software and implemented a concurrent and parallel erasure coding software, called parEC. the proposed parEC process is realized through MPI run time parallel I/O environment and then data placement process is applied to distribute encoded data blocks to their destination storage devices. In this paper, we present the software architecture of parEC. We conduct various performance testing cases on parEC's software components. We present our early experience of using parEC, and address parEC's current status and future development works.

关键词： Erasure coding parallel I/O parallel programming Storage system Power consumption Task parallelism

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Program Autotuning as a Service: Opportunities and Challenges 16

Program Autotuning as a Service: Opportunities and Challenge...

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9th IEEE/ACM international conference on Utility and Cloud computing (UCC)

作者： Sukhoroslov, Oleg Volkov, Sergey Afanasiev, Alexander Russian Acad Sci Inst Informat Transmiss Problems Moscow Russia

ISBN: (纸本)9781450346160

Program autotuning is becoming an increasingly valuable tool for improving performance portability across diverse target architectures, exploring trade-offs between several criteria, or meeting quality of service requirements. Recent work on general autotuning frameworks enabled rapid development of domain-specific autotuners reusing common libraries of parameter types and search techniques. In this work we explore the use of such frameworks to develop general-purpose online services for program autotuning using the Software as a Service model. Beyond the common benefits of this model, the proposed approach opens up a number of unique opportunities, such as collecting performance data and utilizing it to improve further runs, or enabling remote online autotuning. However, the proposed autotuning as a service approach also brings in several challenges, such as accessing target systems, dealing with measurement latency, and supporting execution of user-provided code. this paper presents the first step towards implementing the proposed approach and addressing these challenges. We describe an implementation of generic autotuning service that can be used for tuning arbitrary programs on user-provided computing systems. the service is based on OpenTuner autotuning framework and runs on Everest platform that enables rapid development of computational web services. In contrast to OpenTuner, the service doesn't require installation of the framework, allows users to avoid writing code and supports efficient parallel execution of measurement tasks across multiple machines. the performance of the service is evaluated by using it for tuning synthetic and real programs.

关键词： program autotuning software as a service web services distributed computing

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Proceedings of the 9th EAI international conference on Simulation Tools and Techniques, SIMUTools 2016

Proceedings of the 9th EAI International Conference on Simul...

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9th EAI international conference on Simulation Tools and Techniques, SIMUTools 2016

ISBN: (纸本)9781631901201

the proceedings contain 15 papers. the topics discussed include: fairness-aware update schedules for improving consistency in multi-server distributed virtual environments;design, use and evaluation of P-FSEFI: a parallel soft error fault injection framework for emulating soft errors in parallel applications;Bayesian optimization in high dimensional input space;adaptive synchronization interface for hardware-software co-simulation based on SystemC and QEMU;CloudEval: a simulation environment for evaluating the dynamic cloud VM consolidation;a non-blocking priority queue for the pending event set;implement domain name system (DNS) on network simulator-3;modeling and prediction of software-defined networks performance using queuing Petri nets;and an application of SMC to continuous validation of heterogeneous systems.

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