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检索条件"任意字段=2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing, PDGC 2012"

共 43 条记录，以下是21-30 订阅

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Towards Privacy Preserving Mining over distributed Cloud Databases

Towards Privacy Preserving Mining over Distributed Cloud Dat...

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2nd international conference on Cloud and Green computing / 2nd international conference on Social computing and its Applications (CGC/SCA)

作者： Ibrahim, Ayad Jin, Hai Yassin, Ali A. Zou, Deqing Huazhong Univ Sci & Technol Cluster & Grid Comp Lab Serv Comp Technol & Syst Lab Wuhan 430074 Peoples R China

ISBN: (纸本)9780769548647;9781467330275

Due to great advances in computing and Internet technologies, organizations have been enabled to collect and generate a large amount of data. Most of these organizations tend to analyze their data to discover new patterns. Usually, analyzing such amount of data requires huge computational power and storage facilities that may not be available to these organizations. Cloud computing offers the best way to solve this problem. Storing the private data of different organizations in the same cloud server enhances the mining process, but at the same time, raises privacy concerns. Therefore, it is highly recommended to support privacy preserving data mining algorithms in the cloud environment. This paper introduces an efficient and accurate cryptography-based scheme for mining the cloud data in a secure way without loss of accuracy. Specifically, we address the problem of K-nearest neighbor (KNN) classification over horizontally distributed databases without revealing any unnecessary information. We have utilized the recently developed cryptography primitive, order preserving symmetric encryption (OPSE), to integrate securely the local classifications at a lower cost than the previously presented privacy preserving data mining schemes. Empirical results on real datasets demonstrate that the proposed scheme has similar performance with the naive mining systems in terms of classification accuracy.

关键词： security encryption KNN privacy preserving data mining cloud computing

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Task scheduling through limited duplication with processor utilization in grid computing system

Task scheduling through limited duplication with processor u...

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international conference on parallel distributed and grid computing (pdgc)

作者： Neha Agarwal Chhavi Gupta Ankit Khare Department of CSE and ICT Jaypee University of Information Technology Solan Himachal Pradesh India

In dependent task scheduling algorithms, task duplication is the finest scheduling technique for minimizing the response time of workflow application in grid computing system. When we apply task duplication scheduling algorithm on workflow application, we get shorter schedules (makespan) but it has one limitation that grid node can be overloaded due to duplications of tasks. In this paper we are proposing an algorithm in which we are focusing on three points (1) reducing makespan (2) reducing tasks duplication, and (3) achieving better processor utilization. For this we have suggested an algorithm (TLD-P) which is achieving good results for considered parameters as compared to the existing HLD and EDS-G algorithm.

关键词： Task analysis Nickel Computational modeling

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An evaluation of CUDA-enabled virtualization solutions

An evaluation of CUDA-enabled virtualization solutions

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international conference on parallel distributed and grid computing (pdgc)

作者： M S Vinaya Nagavijayalakshmi Vydyanathan Mrugesh Gajjar International Institute of Information Technology Bangalore Karnataka IN Siemens Corporate Research and Technology Bangalore India

Virtualization, as a technology that enables easy and effective resource sharing with a low cost and energy footprint, is becoming increasingly popular not only in enterprises but also in high performance computing. Applications with stringent performance needs often make use of graphics processors for accelerating their computations. Hence virtualization solutions that support GPU acceleration are gaining importance. This paper performs a detailed evaluation of three frameworks: rCUDA, gVirtuS and Xen, which support GPU acceleration through CUDA, within a virtual machine. We describe the architectures of these three solutions and compare and contrast them in terms of their fidelity, performance, multiplexing and interposition characteristics.

关键词： Acceleration Servers Middleware Linux Virtual machine monitors Bismuth Kernel

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A two-step QoS priority for scheduling in grid

A two-step QoS priority for scheduling in Grid

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international conference on parallel distributed and grid computing (pdgc)

作者： Sanjaya Kumar Panda Pabitra Mohan Khilar Department of Computer Science and Engineering National Institute of Technology Rourkela India

Quality of Service (QoS) is an important property of Scheduling. Demand of QoS is varying from application to application. In the case of scheduling, it is nothing but task and processor requirements. Task requirement refers to bandwidth, speed, operating system, architecture and many more of the processor. But, processor requirement refers to data size, location, deadline, trust level and many more of the task. Our goal is to match and schedule the task-processor pair which leads to reduction in Makespan. In this paper, we propose a two-step QoS priority for scheduling in grid. Bounded and unbounded priorities are introduced as a two-step priority. Based on the priority, tasks are schedule to the processor. Our experiment case shows optimum result than previous scheduling algorithms like Min-Min, QoS guided Min-Min algorithm.

关键词： Quality of service Amplitude shift keying Flowcharts

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parallel Processing of Massive EEG Data with MapReduce

Parallel Processing of Massive EEG Data with MapReduce

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ieee 18th international conference on parallel and distributed Systems (ICPADS)

作者： Wang, Lizhe Chen, Dan Ranjan, Rajiv Khan, Samee U. Kolodziej, Joanna Wang, Jun Chinese Acad Sci Ctr Earth Observat & Digital Earth Beijing 100864 Peoples R China China Univ Geosciences Sch Comp Beijing Peoples R China CSIRO ICT Ctr Informat Engn lab Marshfield 2122 WI USA N Dakota State Univ Dept Elect & Comp Engn Grand Forks ND 58201 USA Univ Technol Inst Comp Sci Krakow Poland Univ Cent Florida Dept Elect Engn & Comp Sci Orlando FL 32816 USA

ISBN: (纸本)9781467345651;9780769549033

Analysis of neural signals like electroencephalogram (EEG) is one of the key technologies in detecting and diagnosing various brain disorders. As neural signals are non-stationary and non-linear in nature, it is almost impossible to understand their true physical dynamics until the recent advent of the Ensemble Empirical Mode Decomposition (EEMD) algorithm. The neural signal processing with EEMD is highly compute-intensive due to the high complexity of the EEMD algorithm. It is also data-intensive because 1) EEG signals contain massive data sets 2) EEMD has to introduce a large number of trials in processing to ensure precision. The MapReduce programming mode is a promising parallel computing paradigm for data intensive computing. To increase the efficiency and performance of the neural signal analysis, this research develops parallel EEMD neural signal processing with MapReduce. In this paper, we implement the parallel EEMD with Hadoop in a modern cyberinfrastructure. Test results and performance evaluation show that parallel EEMD can significantly improve the performance of neural signal processing.

关键词： Data-intensive computing MapReduce parallel processing parallel PROCESSING (COMPUTERS) signal processing Electroencephalography Brain Diseases Key technology MAPPING(MATHEMATICAL) Signal analysis data parallel computing data flow computing

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Resource pricing strategy in wireless grid using non-cooperative bargaining game

Resource pricing strategy in wireless grid using non-coopera...

引用

international conference on parallel distributed and grid computing (pdgc)

作者： Mahantesh N. Birje Sunilkumar S. Manvi Sajal K. Das Department of ISE Basaveshwar Engineering College Bagalkot INDIA Department of ECE REVA ITM Bangalore INDIA University of Texas Arlington TX USA

The consumers in a wireless grid will prefer reliable and cost optimal resources for job execution, while the grid service providers prefer efficient utilization of their resources. Hence brokering of resources that meet the requirements of consumers and providers is a challenging task in presence of unstable (wireless) network connections, market dynamics and rational users. This paper models a resource pricing strategy using a non-cooperative bargaining game for resource allocation considering dynamics in the grid market. The proposed scheme is simulated to evaluate the performance parameters like offered price, surplus, negotiation time and job completion time. We observed that our scheme performs better than existing scheme in terms of negotiation time and job completion time.

关键词： Reliability Dynamic scheduling Servers Equations Mathematical model

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Interoperability of WiFi and WiMAX

Interoperability of WiFi and WiMAX

引用

international conference on parallel distributed and grid computing (pdgc)

作者： Nitul Dutta Sangappa Ramachandra Biradar Sikkim Manipal Institute of Technology Majitar Sikkim India Mody Institute of Technology and Science Laxmangarh Rajasthan India

The aim of this paper is to explore the two most popular wireless networks ieee 802.11 and ieee 802.16 with a view to examine the challenges and issues involved in the integration of both the networks. The 802.11 or Wireless Fidelity (WiFi) is a low cost wireless access technology that supports low data rate within a short range. On the contrary, the ieee 802.16 or WiMAX (Worldwide Interoperability for Microwave Access or) is a costly network that support a data rate of 70Mbps within the range of 50km. To provide guaranteed and satisfactory service quality with moderate cost in wireless environment, integration of the two network technology is necessary. The difference in the MAC layer protocol and routing mechanism the interoperability of the two networks are challenging. In this paper, a brief discussion on WiFi and WiMAX issues are carried out, and investigated various methods and challenges for interoperation of WiFi and WiMAX technology.

关键词： OFDM ieee 802.16 Standards Quality of service WiMAX Frequency modulation Bandwidth

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Improving Matrix Factorization Recommendations for Problems in Big Data 2

Improving Matrix Factorization Recommendations for Problems ...

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2017 ieee 2nd international conference on Big Data Analysis（ICBDA 2017）

作者： Xiaohan Tu Siping Liu Renfa Li College of Computer Science and Electronic Engineering Hunan University

ISBN: (纸本)9781509036202

In the big data environment,recommender systems are facing many problems,such as poor extendibility,data sparseness and low *** this paper,a new collaborative filtering parallel algorithm named NALS-WR is designed in the Linux clusters by using Spark to solve these problems,especially aiming at the bottleneck of processing speed and resource allocation of traditional matrix factorization algorithm in massive data *** experiments were on real Movie Lens *** with other such recommendation systems based on ALS-WR or sigular value decomposition(SVD),our accuracy rate was *** running efficiency was much higher than ALSWR in Hadoop and *** bigger the scale of data,the more efficient it *** to the distributed computing framework and cloud computing environment,our model is more sufficiently ***-WR can improve the execution efficiency of collaborative filtering recommendation algorithm at large data *** experiments also indicated that NALS-WR algorithm was better,whether in extendibility,sparseness resistance or efficiency in the implementation.

关键词： component recommender systems data sparsity problem collaborative filtering alternating-least-squares with Weighted-λ-regularization(ALS-WR)

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Load balanced static grid scheduling using Max-Min heuristic

Load balanced static grid scheduling using Max-Min heuristic

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international conference on parallel distributed and grid computing (pdgc)

作者： Tarun Kumar Ghosh Rajmohan Goswami Sumit Bera Subhabrata Barman Computer Science and Engineering Haldia Institute of Technology Haldia India Computer Applications Pailan College of Management and Technology Kolkata West Bengal India

grid computing, inspired by electrical power grid, is an emerging trend for making easy access to computing resources. Its main objective is to solve computationally hard problems which otherwise cannot be solved by single CPU. This extremely high computing power is achieved by optimal utilization of geographically distributed heterogeneous resources which are lying idle. Load balanced task scheduling is very important problem in complex grid environment. So task scheduling which is one of the NP-Complete problems becomes a focus of research scholars in grid computing area. The traditional Min-Min and Max-Min algorithms are simple algorithms that produces a schedule that minimizes the makespan than the other traditional algorithms in the literature. In real scenario of Min-Min and Max-Min failed to produce a load balanced schedule. The proposed method has two-phases. In the first phase the traditional Max-Min algorithm is executed and in the second phase the tasks are rescheduled to use the unutilized resources effectively.

关键词： Quality of service

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Task scheduling with Load balancing for computational grid using NSGA II with fuzzy mutation

Task scheduling with Load balancing for computational grid u...

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international conference on parallel distributed and grid computing (pdgc)

作者： Reza Salimi Homayun Motameni Hesam Omranpour College of Computer Science Tabari Institute of Higher Education Babol Iran Department of Computer Engineering Islamic Azad University Sari Iran Department of Computer Engineering Amirkabir University of Technology Tehran Iran

The resources management in a grid computing is a complicated problem. Scheduling algorithms play important role in the parallel distributed computing systems for scheduling jobs, and dispatching them to appropriate resources. An efficient task scheduling algorithm is needed to reduce the total Time and Cost for job execution and improve the Load balancing between resources in the grid. In grid computing, load balancing is a technique to distribute workload fairly across computational resources, in order to obtain optimal resource utilization with minimum response time, and avoid overload. Load balancing is a crucial problem to grid computing. In this paper, we address scheduling problem of independent tasks in the market-based grid. In market grids, resource providers can request payment from users based on the amount of computational resource that used by them. Beside we consider Makespan and Load balancing. In this paper, NSGA II with Fuzzy Adaptive Mutation Operator is used to address independent task assignments problems in parallel distributed computing systems. Results obtained proved that our innovative algorithm converges to Pareto-optimal solutions faster and with more quality.

关键词： Vectors Processor scheduling

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