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

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Design and Application of Innovative Teaching Platform Based on Fog computing

Design and Application of Innovative Teaching Platform Based...

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2018 2nd international conference on Education Innovation and Social Science (ICEISS 2018)

作者： Jiejian Cai Baoling Qin Fenglin Zheng Sina Li Yunshi Luo Jianwei Zhang College of Electronic Information Engineering Foshan University

Fog computing is a new type of calculation model in recent years, which shares part of the pressure of cloud computing storage, calculation and processing. Compared with the traditional teaching methods, this paper proposes to use fog computing and big data technology features to build an innovative teaching platform system and the fog model based on fog computing, which can reduce network broadband pressure, reduce the burden on cloud servers, improve comprehensive computing ability, and reduce delay. In addition, it can enhance the exchange of information between teachers and students, guarantee the full range of service levels between teachers and students, and mainly solve the problem of network congestion caused by big data teaching resources. The platform design mainly realizes the functions of resource sharing, teacher-student interaction, effect feedback, intelligent management, etc. Besides, it also can intelligently analyze student behavior, intelligently predict students' favorite courses recommend relevant courses for students to choose, and reform the teaching methods and management modes to improve the interaction between teaching and learning, and improve students' enthusiasm and efficiency in learning.

关键词： cloud computing Fog computing Fog Model distributed computing Innovative Teaching Platform

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A Design of High Performance Simulation Platform

A Design of High Performance Simulation Platform

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2018 2nd international conference on Applied Mathematics, Modeling and Simulation (AMMS 2018)

作者： Jiang ZHU Jun CHEN Chuan-hua WEN Xiang-yuan HUAN Army Command College

Complex system is in high demand for a high-proficiency simulation system to support its simulation use *** this paper,we design a high proficiency simulation platform and develop related technical structure,so as to provide a full-cycle of modeling and simulation(M&S).This architecture are divided into four layer:hardware system layer,parallel operation system layer,simulation service layer and simulation portal *** each layer,M&S technology,which tends towards "networking,virtualization,coordination,service-oriented",are applied in prototype *** bring super computing power,storage power and interaction power,and can give researcher a hint to reconstruct new generation simulation platform.

关键词： Simulation M&S cloud computing High performance

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Unifying Explicit and Implicit Feedback for Top-N Recommendation 2

Unifying Explicit and Implicit Feedback for Top-N Recommenda...

引用

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

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

ISBN: (纸本)9781509036202

In the era of big data,the data are diverse and *** issue that using multi-source data efficiently in recommender system is very *** solve this problem,we proposes a ranking model that integrates explicit feedback data with implicit feedback data *** use weighting factors to measure the impact of different user behaviors on recommendation *** solved the data fusion problem and the Top-N items recommendation *** used matrix decomposition for collaborative ***,a parallel optimization model based on distributed and parallel computing is proposed,and the implementation on Spark is *** comparison with several models,our model greatly enhanced the items recommendation quality and improved the scalability and efficiency of personalized recommender systems.

关键词： component Recommender systems Implicit and explicit feedback Collaborative Filtering Top-N recommendation

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An Incremental Algorithm for Frequent Itemset Mining on Spark 2

An Incremental Algorithm for Frequent Itemset Mining on Spar...

引用

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

作者： Min Yu Chuang Zuo Yunpeng Yuan Yulu Yang College of Computer and Control Engineering Nankai University China Telecom Corporation Limited Beijing Research Institute

ISBN: (纸本)9781509036202

Frequent Itemset Mining is one of the most investigated fields of data *** is expensive to mine frequent itemsets for a large scale data *** when some data is added into the data set,it is still time-consuming from the scratch to re-compute the complete data set to update the frequent itemsets of the data *** to improve the performance of frequent itemset mining for large scale and dynamic data set,we propose a new incremental Apriori algorithm based on *** reuses existing results from previous computation to modify the frequent itemsets according to the newly added data,which avoid massive *** newly proposed algorithm also takes full advantage of distributed resources with the support of *** in theory ensures that the newly proposed algorithm is *** on the real-world data set demonstrate that the newly proposed algorithm effectively avoids reduplicated computation and improves the performance of frequent itemset mining with no additional storage overhead.

关键词： frequent itemset mining apriori incremental computing parallel and distributed processing spark

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Hp-Apriori:Horizontal parallel-Apriori Algorithm For Frequent Itemset Mining from Big Data 2

Hp-Apriori:Horizontal Parallel-Apriori Algorithm For Frequen...

引用

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

作者： Mohammad-Hossein Nadimi-Shahraki Mehdi Mansouri Faculty of Computer Engineering Najafabad branchIslamic Azad University Big Data Research Center Najafabad branchIslamic Azad University

ISBN: (纸本)9781509036202

Due to large scale and complexity of big data,mining the big data using a single personal computer is a difficult *** increasing in the size of databases,parallel computing systems can cause considerable advantages in the data mining applications by means of the exploitation of data mining *** of association rule mining algorithms is an important task in data mining to mine frequent patterns from transaction *** algorithms either distribute database horizontally or increase number of CPU to reduce execution time of frequent pattern *** this paper,a novel frequent itemset mining algorithm,namely Horizontal parallel-Apriori(HP-Apriori),is proposed that divides database both horizontally and vertically with partitioning mining process into four sub-processes so that all four tasks are performed in parallel *** the HPApriori tries to speed up the mining process by an index file that is generated in the first step of *** proposed algorithm has been compared with Count Distribution(CD) in terms of execution time and speedup criteria on the four real *** results demonstrated that the HPApriori outperforms over CD in terms of minimizing execution time and maximizing speedup in high scalability.

关键词： big data frequent itemsets distributed data mining parallel data mining transaction data

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An Energy-aware Virtual Machine Placement Algorithm in cloud Data Center 17

An Energy-aware Virtual Machine Placement Algorithm in Cloud...

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2nd international conference on Intelligent Information Processing (IIP)

作者： Tan, Mingzhe Chi, Ce Zhang, Jiahao Zhao, Shichang Li, Guangli Lu, Shuai Jilin Univ Coll Software 2699 Qianjin St Changchun Jilin Peoples R China Jilin Univ Coll Comp Sci & Technol 2699 Qianjin St Changchun Jilin Peoples R China

ISBN: (纸本)9781450352871

In order to reduce the energy waste in the data center, while taking into account the violation rate of user service level and the resource utilization rate, this paper studies how to adopt effective strategy to get the reasonable suboptimal solution by combining above three indexes. This paper designs a nonlinear energy consumption model based on polynomials and exponents to measure the energy consumption of different deployment schemes. It is the basis of the deployment strategy. At the heart of this paper, the probability transfer function and the fitness function are designed to optimize the ant colony algorithm. Finally a multi-objective optimization ant colony algorithm based on threshold-dependent pheromone updating was proposed. The algorithm is a kind of distributed optimization method, which is beneficial to parallel computation and has a positive feedback mechanism. The optimal solution can be efficiently obtained by continuous updating of pheromone. The experimental results show that the ant colony algorithm of multi-objective virtual machine placement can achieve the optimal trade-off between multiple conflicting targets, so that the system's energy consumption is less, the violation rate of user service level and the resource utilization rate is also small.

关键词： cloud computing Virtual machine Data center Energy saving

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Evaluation of parallel Differential Evolution Implementations on MapReduce and Spark 22nd

引用

22nd international European conference on parallel and distributed computing (Euro-Par)

作者： Teijeiro, Diego Pardo, Xoan C. Penas, David R. Gonzalez, Patricia Banga, Julio R. Doallo, Ramon Univ A Coruna Grp Arquitectura Comp La Coruna Spain CSIC IIM BioProcess Engn Grp Vigo Spain

ISBN: (纸本)9783319589435;9783319589428

Global optimization problems arise in many areas of science and engineering, computational and systems biology and bioinformatics among them. Many research efforts have focused on developing parallel metaheuristics to solve them in reasonable computation times. Recently, new programming models are being proposed to deal with large scale computations on commodity clusters and cloud resources. In this paper we investigate how parallel metaheuristics deal with these new models by the parallelization of the popular Differential Evolution algorithm using MapReduce and Spark. The performance evaluation has been carried out both in a local cluster and in the Amazon Web Services public cloud. The results obtained can be particularly useful for those interested in the potential of new cloud programming models for parallel metaheuristic methods in general and Differential Evolution in particular.

关键词： parallel metaheuristics Differential Evolution cloud computing MapReduce Spark

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cloud engineering Principles and Technology Enablers for Medical Image Processing-as-a-Service

Cloud Engineering Principles and Technology Enablers for Med...

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5th IEEE international conference on cloud engineering (IC2E)

作者： Bao, Shunxing Plassard, Andrew J. Landman, Bennett A. Gokhale, Aniruddha Vanderbilt Univ Dept EECS Nashville TN 37235 USA

ISBN: (纸本)9781509058174

Traditional in-house, laboratory-based medical imaging studies use hierarchical data structures (e.g., NFS file stores) or databases (e.g., COINS, XNAT) for storage and retrieval. The resulting performance from these approaches is, however, impeded by standard network switches since they can saturate network bandwidth during transfer from storage to processing nodes for even moderate-sized studies. To that end, a cloud-based "medical image processing-as-a-service" offers promise in utilizing the ecosystem of Apache Hadoop, which is a flexible framework providing distributed, scalable, fault tolerant storage and parallel computational modules, and HBase, which is a NoSQL database built atop Hadoop's distributed file system. Despite this promise, HBase's load distribution strategy of region split and merge is detrimental to the hierarchical organization of imaging data (e.g., project, subject, session, scan, slice). This paper makes two contributions to address these concerns by describing key cloud engineering principles and technology enhancements we made to the Apache Hadoop ecosystem for medical imaging applications. First, we propose a row-key design for HBase, which is a necessary step that is driven by the hierarchical organization of imaging data. Second, we propose a novel data allocation policy within HBase to strongly enforce collocation of hierarchically related imaging data. The proposed enhancements accelerate data processing by minimizing network usage and localizing processing to machines where the data already exist. Moreover, our approach is amenable to the traditional scan, subject, and project-level analysis procedures, and is compatible with standard command line/scriptable image processing software. Experimental results for an illustrative sample of imaging data reveals that our new HBase policy results in a three-fold time improvement in conversion of classic DICOM to NiFTI file formats when compared with the default HBase region split policy, a

关键词： Hadoop HBase Medical imaging grid computing

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A smart approach for intentional islanding based on dynamic selection algorithm in microgrid with distributed generation 17

A smart approach for intentional islanding based on dynamic ...

引用

2nd international conference on Big Data cloud and Applications, BDCA 2017

作者： Hamdaoui, Youssef Maach, Abdelilah Department of Computer Science Mohammadia Engineering School Mohammed 5 University Rabat Morocco

ISBN: (纸本)9781450348522

The electricity distribution system provides major opportunities for smart grid because of its important role of distributing electrical power from the main grid to users, it has the potential to supply electricity during grid outages. An outage or intentional islanding is one of distribution system problems and we should rethink our concept to include autonomous micro-grid and dynamic distribution concepts with distributed generations. In this condition, it is important for the micro-grid to continue to provide a constant power to the islanded zone load. This paper presents a new approach to power shortages problem and specifies the goals of strategy can be in an intentional-islanding operation to improve public access to power and provide consumer power during emergencies and grid outage, we explain in this paper a potential outage management approach and determine the best way to distribute the planned outages among the consumers, the planning should cover all entities in the islanded zone but our goal is to have the minimum loss and the maximum consumer covered. We build our smart distribution network based on consumer parameters like geographic coordinates, energy produced, emergency load, optional load, energy produced and category. When the micro-grid is cut off from the main grid the system detect the most emergency entity and take this entity as start point to build a dynamic planning, each entity near of the entity reference will be is added to the network tree if his emergency load is covered by the local distributed generator. As result of emergency strategy we obtain an outage distribution network for the intentional islanding. An intelligent algorithm is developed to solve the problem. We also discuss some results of the different distribution model. © 2017 Association for computing Machinery.

关键词： Outages

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A Visual Model-based Evaluation Framework of cloud-based Prognostics and Health Management 2

A Visual Model-based Evaluation Framework of Cloud-based Pro...

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2nd IEEE international conference on Smart cloud (Smartcloud)

作者： Mao, Kedun Zhu, Yongxin Chen, Zhixiong Tao, Xiang Xue, Qixuan Wu, Han Mao, Yishu Hou, Junjie Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai Peoples R China Commercial Aircraft Corp China Ltd Shanghai Peoples R China Chinese Acad Sci Shanghai Adv Res Inst Beijing Peoples R China

ISBN: (纸本)9781538636848

Nowadays, systems for various smart city industries such as city power plants, public transportation and integrated modular avionics are becoming increasingly complicated, with most of components being embedded and geologically distributed. In order to ensure the availability of target systems, prognostic and health management develops as an important system to assess the current health state and estimate the future health state based on modern Industrial Internet of Things (IIoT) and cloud computing technologies. The early design of PHM systems requires system engineering methodology to ensure the robustness and effectiveness of systems. However, as the complexity grows, there may be some misunderstanding in specification that are not obvious and it is hard to perform verification and evaluation in a more intuitive way. In order to enhance the intuitiveness and reduce the misunderstanding in early development stage, we present a visual model-based framework to simulate and evaluate the cloud-based prognostics and health management systems. The framework proposes a three-abstraction-layer hierarchical architecture to represent distributed data sources and cloud-based PHM service center. The design of the framework is based on system modeling language and allows flexible algorithm implementations of function modules. The simulation of framework is visualized through the animated behavior diagrams. Furthermore, we propose a performance evaluation and measurement method combining quality of maintenance analysis and cost-benefit analysis for PHM systems.

关键词： prognostics and health management framework simulation system engineering performance evaluation

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