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

共 1765 条记录，以下是411-420 订阅

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Scalable parallel quadrilateral mesh generation coupled with mesh partitioning

Scalable parallel quadrilateral mesh generation coupled with...

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6th international conference on parallel and distributed computing, applications and technologies (PDCAT 2005)

作者： Chen, JJ Zheng, Y Ning, X Zhejiang Univ Ctr Engn & Sci Computat Hangzhou 310027 Zhejiang Peoples R China Zhejiang Univ Coll Comp Sci Hangzhou 310027 Zhejiang Peoples R China

ISBN: (纸本)0769524052

In this paper, we present our efforts to parallelize an unstructured quadrilateral mesh generator. Its serial version is based on the divider-and-conquer idea, and mainly includes two stages, i.e. geometry decomposition and mesh generation. Both stages are parallelized separately. A highly efficient fine-grain level parallel scheme is presented to parallelize the stage of geometry decomposition. A SubDomain Graph (SDG), which represents the connections of subdomains, is constructed the task of parallel mesh generation is then reduced to that of the SDG partitioning. Since the number of elements in subdomains could be pre-computed before meshing, a static load balancing scheme to partition the SDG performs well with the aid of Metis tools. Numerical results show that scalable timing performance could be achieved by using the parallel mesh generator with resulting meshes nicely partitioned among processors, which enables a fast parallel simulation environment by eliminating the traditional 110-busy process of mesh repartitioning.

关键词： parallel processing systems

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A Hybrid parallel Implementation for the Maximum Flow Problem 26

A Hybrid Parallel Implementation for the Maximum Flow Proble...

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26th Euromicro international conference on parallel, distributed, and Network-Based Processing (PDP)

作者： Stefanes, Marco A. Alvino, Luiz F. Univ Fed Mato Grosso do Sul Comp Coll Campo Grande Brazil Univ Fed Mato Grosso do Sul Campo Grande Brazil

ISBN: (纸本)9781538649756

the maximum flow problem is a classical combinatorial problem with many applications. In this work a hybrid parallel algorithm using both multi-core and many-core technologies for computing the maximum flow in a network is presented. the proposed implementation is applicable in OpenMP/CUDA-enabled computing environment. To improve the performance two strategies were implemented: an adaptive approach where the algorithm alternate GPU/CPU processing according to the number of active nodes and implementations of the global relabeling and gap relabeling heuristics on multi-core approach. When compared against the best sequential implementation, the speedups range from 2.36 to 5.38 in several kinds of graph. Results show that the proposed algorithm is faster than previous parallel implementations on CPU/GPUs for all kinds of tested graphs.

关键词： Maximum flow Push-relabel method Hybrid parallel programming Multi/many-core architectures

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Track Chair's Report: Convergence of distributed Clouds, Grids and their Management CDCGM 2017 Cloud Native or Cloud Agnostic? that is the Question in 2017 WETICE2017 Poznan, Poland, June 21-23, 2017 26

Track Chair's Report: Convergence of Distributed Clouds, Gri...

引用

26th IEEE international conference on Enabling technologies - Infrastructure for Collaborative Enterprises (WETICE)

作者： Messina, Fabrizio Mikkilineni, Rao Morana, Giovanni Rosaci, Domenico Univ Catania Dept Math & Informat Vle Andrea Doria 6 I-95125 Catania Italy C3DNA Inc Santa Clara CA USA C3DNA Inc R&D & Engn Catania Italy Univ Reggio Calabria DICEAM Dept Reggio Di Calabria RC Italy

ISBN: (纸本)9781538617595

this track started in 2009 with opening remarks from the Chair observing that the computing cloud evolution depends on research efforts from the infrastructure providers creating next generation hardware that is service friendly, service developers that embed business service intelligence in the computing infrastructure to create distributed business workflow execution services and service providers who assure service delivery on a massive scale with global interoperability. the state of the art architecture and evolution of the cloud at that time was already increasing datacenter complexity by piling up new layers of management over the many layers that already exist. Since then, the scale of distributed applications and their management have taken a new dimension demanding tolerance to wild fluctuations both in workloads and available computing resource pools. there are many calls to go cloud native and architect applications using the many services provided by the cloud providers such as Amazon Web Services. On the other hand, there are also calls for avoiding vendor lock-in by going multi-cloud and becoming cloud agnostic. In this conference there is a new paper that proposes cloud agnostic approach with globally interoperable cloud network using private or public network while reducing the complexity of Virtual machine image motion across clouds. In addition, there are 7 papers describing advances in current distributed and cloud computing practices dealing with quality of service, adaptive algorithms and software defined network architectures.

关键词： Cloud computing grid computing distributed Intelligent Managed Element Networks distributed Services Management Services Virtualization parallel computing

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An Unsupervised Approach for Online Detection and Mitigation of High-Rate DDoS Attacks Based on an In-Memory distributed Graph Using Streaming Data and Analytics 17

An Unsupervised Approach for Online Detection and Mitigation...

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10th international conference on Utility and Cloud computing (UCC) / 4th international conference on Big Data computing, applications and technologies (BDCAT)

作者： Villalobos, J. J. Rodero, Ivan Parashar, Manish Rutgers Univ State Univ New Jersey Rutgers Discovery Informat Inst Piscataway NJ 08854 USA

ISBN: (纸本)9781450355490

A distributed Denial of Service (DDoS) attack is an attempt to make an online service, a network, or even an entire organization, unavailable by saturating it with traffic from multiple sources. DDoS attacks are among the most common and most devastating threats that network defenders have to watch out for. DDoS attacks are becoming bigger, more frequent, and more sophisticated. Volumetric attacks are the most common types of DDoS attacks. A DDoS attack is considered volumetric, or high-rate, when within a short period of time it generates a large amount of packets or a high volume of traffic. High-rate attacks are well-known and have received much attention in the past decade;however, despite several detection and mitigation strategies have been designed and implemented, high-rate attacks are still halting the normal operation of information technology infrastructures across the Internet when the protection mechanisms are not able to cope with the aggregated capacity that the perpetrators have put together. With this in mind, the present paper aims to propose and test a distributed and collaborative architecture for online high-rate DDoS attack detection and mitigation based on an in-memory distributed graph data structure and unsupervised machine learning algorithms that leverage real-time streaming data and analytics. We have successfully tested our proposed mechanism using a real-world DDoS attack dataset at its original rate in pursuance of reproducing the conditions of an actual large scale attack.

关键词： DDoS Detection DDoS Mitigation Machine Learning distributed Big Data Analytics

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Managing Heterogeneity in Model-Based Systems Engineering of Cyber-Physical Systems 10

Managing Heterogeneity in Model-Based Systems Engineering of...

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10th international conference on P2P, parallel, Grid, Cloud and Internet computing 3PGCIC

作者： Van Acker, Bert Denil, Joachim Vangheluwe, Hans De Meulenaere, Paul Univ Antwerp Constrained Syst Lab CoSys Lab Antwerp Belgium Univ Antwerp Ansymo Antwerp Belgium

ISBN: (纸本)9781467394734

Model-based Systems Engineering plays a pivotal role in the design of distributed embedded systems by enabling early virtual integration of the different parts of the system. Traditionally, the system model is composed of subsystem models at the same level of abstraction and with one particular view. However, in some cases the system model may comprise subsystem models at different levels of abstraction. Integration of these different abstraction level models imposes some important drawbacks which hinder the overall system simulations. these drawbacks need to be addressed to facilitate the simulation of systems composed with multi-level subsystem models. In this paper we report on modelling techniques for embedded and distributed systems to deal with this heterogeneity. We describe a methodology to (semi-)automatically generate an executable multi-level system simulation model starting from an abstract system architecture of the system. A platooning system example is used to demonstrate the new modelling techniques.

关键词： Cyber-physical systems distributed Embedded Systems Model-Driven Engineering

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A QoS Scheduling Scheme with Availability Constraint in distributed Systems

A QoS Scheduling Scheme with Availability Constraint in Dist...

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13th international conference on parallel and distributed computing, applications, and technologies (PDCAT)

作者： Tong, Zhao Li, Kenli Xiao, Zheng Qin, Xiao Hunan Univ Coll Informat Sci & Engn Changsha 410082 Hunan Peoples R China Auburn Univ Dept Comp Sci & Software Engn Auburn AL USA

ISBN: (纸本)9780769548791

An efficient resource management mechanism is important in a heterogeneous system to discover available resources, to allocate an appropriate subset of resources to applications, and to map data or tasks onto selected resources. the key component, tasks scheduling, draws our attention. Makespan is the principal concern many existing researches. But, other QoS requirements are also important in more and more realistic applications. Like Grid service it is expected that the service provider be reliable, robust, or highly available. In this study, an existing availability-aware scheduling model called SSAC is investigated first. then, we proposed an optimization approach to increase the availability and to reduce the makespan of tasks running in heterogeneous systems. three quantitative conditions are used to guide the optimization. Our experimental results show that compared with three existing solutions (Minmin, SSAC and ACO), our algorithm significantly improves the availability and performance of multiclass tasks running in heterogeneous systems.

关键词： Heterogeneous systems Task scheduling QoS Scheduling Availability

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A distributed genetic algorithm with adaptive diversity maintenance for ordered problems 20

A distributed genetic algorithm with adaptive diversity main...

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20th international conference on parallel and distributed computing, applications and technologies, PDCAT 2019

作者： Ohira, Ryoma Islam, Md. Saiful School of Information Communication and Technology Griffith University Southport Australia

ISBN: (纸本)9781728126166

Maintaining population diversity is critical to the performance of a Genetic Algorithm (GA). Applying appropriate strategies for measuring population diversity is important in order to ensure that the mechanisms for controlling population diversity are provided with accurate feedback. Sequence-wise approaches to measuring population diversity have demonstrated their effectiveness in assisting with maintaining population diversity for ordered problems, however these processes increase the computational costs for solving ordered problems. Research in distributed GAs have demonstrated how applying different distribution models can affect an GA's ability to scale and effectively search the solution space. this paper proposes a distributed GA with adaptive parameter controls for solving ordered problems such as the travelling salesman problem(TSP), capacitated vehicle routing problem (CVRP) and the job-shop scheduling problem (JSSP). Extensive experimental results demonstrate the superiority of the proposed approach. © 2019 IEEE.

关键词： Traveling salesman problem

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On using provenance data to increase the reliability of ubiquitous computing environments 08

On using provenance data to increase the reliability of ubiq...

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10th international conference on Information Integration and Web-based applications and Services, iiWAS 2008

作者： Imran, Muhammad Hummel, Karin Anna Department of Distributed and Multimedia Systems Lenaugasse 2/8 A-1080 Wien Austria

ISBN: (纸本)9781605583495

Ubiquitous computing aims at providing computing functionalities embedded into everyday life. technologies such as networked sensors, actuators, mobile devices, appliances, and stationary computing infrastructures are intended to support smart services by making use of context information. this information may be only of interest for the moment the service is provided, like location-based services, or collected for later use, e.g., to optimize logistic workflows. In particular in case of spontaneous interactions of components, it becomes difficult to keep track about the provenance of sensor data or even services that are provided in a particular situation. If problems occur, like privacy and security attacks or service failures, this lack of traceable information may decrease the trustworthiness of systems and legal requirements might not be fulfilled properly. In this position paper, we introduce provenance data to increase reliability in ubiquitous computing systems. Hereby, provenance is a summary of the historical information about gathering, collecting, and aggregating data. We demonstrate and motivate the usefulness of the approach and discuss open issues and further research directions by presenting a health-care emergency use case. Copyright 2008 ACM.

关键词： Ubiquitous computing

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MapReduce implementation of prestack kirchhoff time migration (PKTM) on seismic data

MapReduce implementation of prestack kirchhoff time migratio...

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2011 12th international conference on parallel and distributed computing, applications and technologies, PDCAT 2011

作者： Rizvandi, Nikzad Babaii Boloori, Ali Javadzadeh Kamyabpour, Najmeh Y.zomaya, Albert Centre for Distributed and High Performance Computing School of Information Technologies University of Sydney NSW 2006 Australia Australian Technology Park Sydney NSW 1430 Australia INEXT-Centre for Innovation in IT Services and Applications University of Technology Sydney NSW 2007 Australia

ISBN: (纸本)9780769545646

the oil and gas industries have been great consumers of parallel and distributed computing systems, by frequently running technical applications with intensive processing of terabytes of data. By the emergence of cloud computing which gives the opportunity to hire high-throughput computing resources with lower operational costs, such industries have started to adopt their technical applications to be executed on such high-performance commodity systems. In this paper, we first give an overview of forward/inverse Prestack Kirchhoff Time Migration (PKTM) algorithm, as one of the well-known seismic imaging algorithms. then we will explain our proposed approach to fit this algorithm for running on Google's MapReduce framework. Toward the end, we will analyse the relation between MapReduce-based PKTM completion time and the number of mappers/reducers on pseudo-distributed MapReduce mode. © 2011 IEEE.

关键词： MapReduce

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HyperPRAW: Architecture-Aware Hypergraph Restreaming Partition to Improve Performance of parallel applications Running on High Performance computing Systems 19

HyperPRAW: Architecture-Aware Hypergraph Restreaming Partiti...

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48th international conference on parallel Processing (ICPP)

作者： Musoles, Carlos Fernandez Coca, Daniel Richmond, Paul Univ Sheffield Sheffield S Yorkshire England

ISBN: (纸本)9781450362955

High Performance computing (HPC) demand is on the rise, particularly for large distributed computing. HPC systems have, by design, very heterogeneous architectures, both in computation and in communication bandwidth, resulting in wide variations in the cost of communications between compute units. If large distributed applications are to take full advantage of HPC, the physical communication capabilities must be taken into consideration when allocating workload. Hypergraphs are good at modelling total volume of communication in parallel and distributed applications. To the best of our knowledge, there are no hypergraph partitioning algorithms to date that are architecture-aware. We propose a novel restreaming hypergraph partitioning algorithm (HyperPRAW) that takes advantage of peer to peer physical bandwidth profiling data to improve distributed applications performance in HPC systems. Our results show that not only the quality of the partitions achieved by our algorithm is comparable with state-of-the-art multilevel partitioning, but that the runtime performance in a synthetic benchmark is significantly reduced in 10 hypergraph models tested, with speedup factors of up to 14x.

关键词： datasets neural networks gaze detection text tagging

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