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检索条件"任意字段=2nd International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering"

共 1404 条记录，以下是701-710 订阅

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Deadline-constrained workflow scheduling using imperialist competitive algorithm on infrastructure as a service clouds 2

Deadline-constrained workflow scheduling using imperialist c...

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2nd international conference on Knowledge Based engineering and Innovation (KBEI)

作者： Arshad, Reza Rafeh, Reza Arak Univ Dept Comp Engn Arak Iran

ISBN: (纸本)9781467365062

cloud computing is internet based computing paradigm that opens new opportunities for researchers to investigate its benefits and disadvantages on executing scientific applications such as workflow s. Workflow scheduling on distributed systems has been widely studied over the years. Most of the proposed scheduling algorithms attempt to minimize the execution time without considering the cost of accessing resources and mostly target environments similar or equal to community grids. But, in case of cloud computing, usually, faster resources are more expensive than the slower one such that execution time as well as cost incurred by using a set of heterogeneous resources over cloud should be minimized. The proposed approach in this paper is based on Imperialist Competitive Algorithm (ICA). The ICA is a new evolutionary algorithm which is inspired by human's socio-political evolution. Generally this algorithm mathematically models the imperialism as a level of human's social evolution and uses this model for optimization Problems. In this paper, we develop a static cost-minimization, deadline constrained heuristic for scheduling a scientific workflow application in a cloud environment. Our approach considers fundamental features of IaaS providers such as on-demand resource provisioning and unlimited computing resources. The results show that our approach performs better than the PSO algorithm in terms of cost minimization and percent of meeting deadline.

关键词： cloud computing IaaS Scheduling Workflow Imperialist Competitive Algorithm

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A4SDN-Adaptive Alienated Ant Algorithm for Software-Defined Networking 10

A4SDN-Adaptive Alienated Ant Algorithm for Software-Defined ...

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10th international conference on P2P, parallel, grid, cloud and Internet computing 3PGCIC

作者： Di Stefano, Antonella Cammarata, Giovanni Morana, Giovanni Zito, Daniele Univ Catania DIEEI I-95124 Catania Italy

ISBN: (纸本)9781467394734

This paper introduces A4SDN, a distributed, adaptive, load-balancing algorithm for traffic engineering on SoftwareDefined Networks. A4SDN, i. e. the Adaptive Alienated Ant Algorithm for Software-Defined Networking, is based on the Alienated Ant Algorithm (AAA), a stochastic-based, heuristic approach used to solve combinatorial and multi-constraint optimisation problems. Based on a non natural ants' behaviour, the AAA forces the ants in searching for food to distribute themselves over all the available paths rather than converge to a single one. This strategy, applied to the packets to route, supplies an autonomic dynamic routing and leads to a better exploitation of the network bandwidth, enforcing best effort traffic and improving network performance. A comparison between A4SDN with two Dijkstrabased routing solutions clearly shows that A4SDN is able to guarantee a higher throughput associated with a lower delay and packet loss rate.

关键词： software defined networking (SDN) alienated ant algorithm dijkstra load balancing routing algorithm traffic engineering

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Research of SSO Based on the Fingerprint Key in cloud computing 2

Research of SSO Based on the Fingerprint Key in Cloud Comput...

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2nd FTRA international conference on Ubiquitous computing Application and Wireless Sensor Network (UCAWSN)

作者： Zhang, Yong-Sheng Zou, Jia-Shun Gao, Yan Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Peoples R China Shandong Prov Key Lab Novel Distributed Comp Soft Jinan 250014 Peoples R China

ISBN: (纸本)9789401796187;9789401796170

To solve the problem of single sign-on and to realize the destination of fast access, an improved single sign-on system is presented, which is based on the combination between biometric key technology and elliptic curve cryptography. The system analyses the mechanism of status register and verification, which is based on the platform of cloud sign-on. The system needs dual authentication of both fingerprint and password. What's more, it adopts a two-way authentication. So it has strong security, and it can resist replay attack and decimal attack effectively.

关键词： Single sign-on Elliptic curve Fingerprint verification cloud computing

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Tunable Performance and Consistency Tradeoffs for Geographically Replicated cloud Services (COLOR) 2

Tunable Performance and Consistency Tradeoffs for Geographic...

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2nd IEEE international conference on Cyber Security and cloud computing, CScloud 2015

作者： Zhu, Wenbo Woodside, Murray Systems and Computer Engineering Carleton University Ottawa Canada

ISBN: (纸本)9781467392990

COLOR (client-oriented layered optimistic replication) is a combination of optimistic and conservative data replication that allows cloud services to be replicated across widely distributed locations without suffering from the latency overhead of strict algorithms, and with quantifiable and controllable tradeoffs between performance and consistency guarantees. The COLOR solution adopts a layered approach to enable optimistic delivery of client messages on top of any existing storage layer that manages the strict replication of the cloud service. When clients may be temporarily exposed to inconsistent states due to replication failures, such inconsistency is made recoverable similar to "optimistic concurrency control" for clients that cache the server state. COLOR supports different numeric parameters to trade the strict consistency for better performance to possibly match Eventual Consistency, while the end-to-end consistency is always guaranteed as the storage layer will never deliver any client messages generated from inconsistent states. © 2015 IEEE.

关键词： Commerce

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2nd international conference on Computer, Intelligent and Education Technology, CICET 2015

2nd International Conference on Computer, Intelligent and Ed...

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2nd international conference on Computer, Intelligent and Education Technology, CICET 2015

ISBN: (纸本)9781138028005

The proceedings contain 230 papers. The special focus in this conference is on Computer Science, Intelligent computing, Mechanical, Energy, Information and Education engineering. The topics include: Texture image-based 3D entity modeling method;the query optimization algorithm based on distributed heterogeneous database;design and implementation of mobile learning system based on cloud computing;evaluation method for e-commerce transaction credit based on cloud model;the design and implementation of intelligent home control system;design and analyze a worktable motion control system;application of newton interpolation in static nonlinear correction for MAF sensor;improved method for the recovery of regular broken paper;the design of intelligent hydraulic vulcanizing machine control system;driving habits analysis on vehicle data using error back-propagation neural network algorithm;use of cloud computing for distributed simulation;research of the color descriptor sift;analysis of computer-aided design of the detector appearance;design of Ip core of DPSK modulator with variable bit rate and carrier frequency based on FPGA;design and implementation of remote control-based autonomous collision avoidance system prototype;modeling and analysis of uphill climbing for the electromagnetic-driven spherical robot;starting performance simulation system of the three-phase synchronous and asynchronous motors based on matlab;the application of online examination system of medical science in hospitals;building image classification methodology using gaussian kernel combined with nonparametric kernel and research on the image measurement method of cycloidal gear pitch deviation based on openCV.

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Running high resolution coastal forecasts: Moving from grid to cloud resources

Running high resolution coastal forecasts: Moving from grid ...

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15th international conference on Civil, Structural and Environmental engineering computing, CIVIL-COMP 2015

作者： Rogeiro, J. Azevedo, A. Rodrigues, M. Oliveira, A. Hydraulics and Environment Department National Laboratory of Civil Engineering Lisbon Portugal

Computational forecast systems (CFS) are essential tools for daily and emergency coastal management by providing water dynamics predictions, through integration of numerical models and field data. The reliability of their predictions depends greatly on the parallel models' accuracy, but achieving the adequate resolution in spatial discretizations for port-to-ocean, multi-scale analysis is often hampered by computational costs. Nowadays forecast systems are processed in dedicated workstations, fulfilling robustness and quality control through automatic comparison with field data and simulation redundancy. Recently, CFS has been ported to HPC grids with significant success, but requiring highly-specialized staff to maintaining them in these complex environments. The need to increase the available resources and to export CFS to coastal managers has promoted the search for simpler approaches. The scalability and flexibility of cloud resources, along with dedicated services for facilitating their use, makes them an attractive option. In this paper, the performance of operational coastal forecast systems are assessed and compared for the first time in multiple environments, including local workstations, grids and a pilot cloud. The analysis is conducted in a range of resources from the physical processor number available at the cloud to the optimal number of processors for the specific cases. ©Civil-Comp Press, 2015.

关键词： Numerical models

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2nd international conference on cloud computing and Big Data, cloudCom-Asia 2015

2nd International Conference on Cloud Computing and Big Data...

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2nd international conference on cloud computing and Big Data, cloudCom-Asia 2015

ISBN: (纸本)9783319284293

The proceedings contain 29 papers. The special focus in this conference is on cloud Architecture, Applications, Big Data and Social Network. The topics include: An effective approach to isolating performance bottleneck during slow data delivery;schedule compaction and deadline constrained dag scheduling for IAAS cloud;synthesizing realistic cloud workload traces for studying dynamic resource system management;energy-efficient VM placement algorithms for cloud data center;a new analytics model for large scale multidimensional data visualization;an architecture-based autonomous engine for services configuration and deployment in hybrid clouds;dynamic load sharing to maximize resource utilization within cloud federation;real-time task scheduling algorithm for cloud computing based on particle swarm optimization;making GPU warp scheduler and memory scheduler synchronization-aware;a novel grid based k-means cluster method for traffic zone division;color image fusion researching based on S-PCNN and laplacian pyramid;rationalizing the parameters of k-nearest neighbor classification algorithm;analyzing and predicting failure in hadoop clusters using distributed hidden Markov model;emerging pragmatic patterns in large-scale RDF data;cross-correlation as tool to determine the similarity of series of measurements for big-data analysis tasks;the key technologies of real-time processing large scale microblog data stream;an efficient index method for multi-dimensional query in cloud environment;keyword search over encrypted data in cloud computing from lattices in the standard model and research of terminal transparent encryption storage mechanism for multi-cloud disks.

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CUDAGA: A portable parallel programming model for GPU cluster 2nd

CUDAGA: A portable parallel programming model for GPU cluste...

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2nd international conference on cloud computing and Big Data, cloudCom-Asia 2015

作者： Chen, Yong Jin, Hai Xu, Dechao Zheng, Ran Liu, Haocheng Zeng, Jingxiang Services Computing Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China China Electric Power Research Institute Beijing100192 China

ISBN: (纸本)9783319284293

GPU cluster is important for high performance computing with its high performance/cost ratio. However, it is still very hard for application developers to write parallel codes on GPU. MPI is mostly used for parallel programming, and data locality and communication must be specified explicitly by developers. Moreover, data transmission between CPU and GPU must also be processed with CUDA codes. CUDAGA, a new parallel programming model for GPU cluster with CUDA, is presented to provide portable interfaces for communication on GPUs. GA (Global Arrays), a portable shared-memory programming model for distributed memory computers, is the base to facilitate parallel programming and maintain transparent global arrays on GPUs. Experiments show that CUDAGA can decrease parallel programming difficulties, but ensures better performance for some specific applications. © Springer international Publishing Switzerland 2015.

关键词： Graphics processing unit

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Accelerating Monte Carlo Simulation of Neutron Transport on the Intel MIC architecture 2

Accelerating Monte Carlo Simulation of Neutron Transport on ...

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2nd international conference on Information Science and Control engineering

作者： Cui, Xiantao Liu, Jie Chi, Lihua Wang, Qinglin Natl Univ Def Technol Sci & Technol Parallel & Distributed Proc Lab Changsha 410073 Hunan Peoples R China

ISBN: (纸本)9781467368506

Simulation of particle transport is critical for a great many of scientific and engineering domains. The Monte Carlo ( MC) method is one of the most important numerical methods for the simulation of particle transport, and can simulate many complex types of particle transport. But the computation requirement of the MC simulation is very large. In 2010, Intel announced the Intel Many Integrated Core (MIC) architecture, which consists of many simple general-purpose cores and supports the well-known shared-memory execution model that is the base of most nodes in HPC machines. On account of the independence of simulation of each particle in the MC method, it is well-suited to accelerate the MC simulation on MIC. In this paper, an algorithm named MCNP-MIC based MIC is presented for MC simulation of neutron transport in the context of deep penetration problem, which includes the development of parallel random generator, the assignment of particle number based thread number and the design of high efficiency data structures for parallelism. Eventually, we get the results as follows: with the same problem scale and computational accuracy, the MCNP-MIC algorithm has achieved roughly 5.6-fold speedup running on a 57-core MIC chip in comparison with the serial MCNP algorithm on an Intel Xeon E5-2670 CPU.

关键词： Monte Carlo Neutron transport MCNP Many Integrated Core (MIC) architecture parallel computing

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Evaluation of Machine Learning Frameworks on Bank Marketing and Higgs Datasets 2

Evaluation of Machine Learning Frameworks on Bank Marketing ...

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2nd IEEE international conference on Advances in computing and Communication engineering (ICACCE)

作者： Shashidhara, Bhuvan M. Jain, Siddharth Rao, Vinay D. Patil, Nagamma Raghavendra, G. S. Natl Inst Technol Karnataka Dept Informat Technol Surathkal India

ISBN: (纸本)9781479917341

Big data is an emerging field with different datasets of various sizes are being analyzed for potential applications. In parallel, many frameworks are being introduced where these datasets can be fed into machine learning algorithms. Though some experiments have been done to compare different machine learning algorithms on different data, these experiments have not been tested out on different platforms. Our research aims to compare two selected machine learning algorithms on data sets of different sizes deployed on different platforms like Weka, Scikit-Learn and Apache Spark. They are evaluated based on Training time, Accuracy and Root mean squared error. This comparison helps us to decide what platform is best suited to work while applying computationally expensive selected machine learning algorithms on a particular size of data. Experiments suggested that Scikit-Learn would be optimal on data which can fit into memory. While working with huge, data Apache Spark would be optimal as it performs parallel computations by distributing the data over a cluster. Hence this study concludes that spark platform which has growing support for parallel implementation of machine learning algorithms could be optimal to analyze big data.

关键词： Machine Learning Algorithms Big Data parallel Execution distributed computing WEKA Scikit-Learn Apache Spark

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