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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571-580 订阅

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Simulation of Short Take-Off and Vertical Landing (STOVL) Aircraft in 5G OGCE 2

Simulation of Short Take-Off and Vertical Landing (STOVL) Ai...

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2nd international conference on Robotics and Automation engineering (ICRAE)

作者： Lu, Zhi Yuan, Mingzhe Lu, Yi Wang, Zhongfeng Tianjin Univ Technol & Educ Sch IT & Engn Tianjin 300222 Peoples R China Chinese Acad Sci Shenyang Inst Automat Shenyang 110016 Liaoning Peoples R China

ISBN: (纸本)9781538613061

Based on the fifth generation mobile communication (5G), 5G open grid computing environment (5G OGCE), simulation of short take-off and vertical landing (STOVL) aircraft is presented in this paper. And the development of STOVL aircraft has always been a focus, and its performance is a challenge. So far, the type of STOVL aircraft that can be used on the battlefield is the F-35 Lightning II and Marine AV-8B (Harrier Jump Jet). The stability of STOVL aircraft is an important index and parameters. A robot system with turbofan engine is also presented to improve and possess the STOVL capability of J-11fighter, J-15 naval fighter and Shenyang J-16 strike fighter. The robot system with the turbofan engine and the Shenyang J-16 strike fighter constitute the model of the STOVL aircraft, and this model is applied to realization the STOVL flight simulation of commercial large wide-bodied aircraft in 5G OGCE.

关键词： 5G open grid computing environment (5G OGCE) short take-off and vertical landing (STOVL) hand type vertical jet nozzle robot balance tail robot aircraft design robotics turbofan and robots MPP simulation in 5G OGCE distributed artificial intelligence (distributed AI) software architecture and engineering

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cloud computing Resource Scheduling based on Improved Semantic Search Engine 17

Cloud Computing Resource Scheduling based on Improved Semant...

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2nd international conference on Intelligent Information Processing (IIP)

作者： Chen, Jia Xu, Jiali Hui, Bei Univ Elect Sci & Technol China Sch Informat & Software Engn Chengdu 610054 Sichuan Peoples R China Chengdu Univ Sch Informat Sci & Engn Chengdu 610106 Sichuan Peoples R China

ISBN: (纸本)9781450352871

cloud computing resource has the features of dynamic, heterogeneous, distributed and complexity etc. Meanwhile the numbers of resources and tasks to be scheduled in cloud are usually variable. This makes the cloud resource scheduling a complex optimization problem. None of existing cloud systems is both being an automated scheduling and considering the optimal usage of resources. To address above problems, we propose a cloud computing resource scheduling strategy using improved Semantic Search Engine (ISSE). SSE is a new type of service search engine developed by Semantic computing laboratory in University of California, Irvine. It provides cloud users with a friendly problem-driven interface to automatically schedule resources that would be used to build a solution according to users' requirements in the aid of semantic information from resources and user requirements. Further we adopt improved genetic algorithm(IGA) in SSE to optimize the scheduling so as to obtain the optimal usage of resources. In our proposed IGA there should be a code distant between the selected parents to retain the population diversity and obtain the valid solution. The architecture of our proposed ISSE is presented as well as the process and implementation of IGA. The experiment results show our proposed ISSE is feasible and can reduce about 16% average tasks execution time comparing to the traditional cloud resource scheduling (TCRS).

关键词： cloud computing Resource Scheduling Improved Semantic

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Spectral-Spatial Classification of Hyperspectral Image Using distributed Extreme Learning Machine with MapReduce 2

Spectral-Spatial Classification of Hyperspectral Image Using...

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

作者： Jinmei Shi Junhua Ku Department of Information Engineering Hainan Institute of Science & Technology

ISBN: (纸本)9781509036202

ELM and Map Reduce has an unparalleled advantage of other similar technologies,which attract widely attention in machine learning and distributed data processing communities *** this paper,we combine the advantage of ELM and Map Reduce,and propose a distributed Extreme Learning Machine based on Map Reduce framework(DELMM),which makes full use of the parallel computing ability of Map Reduce framework and realizes efficient learning of large-scale training *** particular,we present a spectral-spatial DELMM-based classifier for hyperspectral remote sensing images that integrates the information provided by extended morphological *** proposed spectral-spatial classifier allows different weights for both(spatial and spectral) features outperforming other ELMbased classifiers in terms of accuracy for land cover *** accuracy classification results are also better than those obtained by equivalent spectral-spatial SVM-based classifiers.

关键词： Gabor filter hyperspectral image classification spectral-spatial analysis distributed extreme learning machine

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Transaction Scheduling for Software Transactional Memory 2

Transaction Scheduling for Software Transactional Memory

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2nd IEEE international conference on cloud computing and Big Data Analysis (ICCCBDA)

作者： Popovic, Miroslav Kordic, Branislav Basicevic, Ilija Univ Novi Sad Fac Tech Sci Trg Dositeja Obradovica 6 Novi Sad 21000 Serbia

ISBN: (纸本)9781509044993

Over the last two decades, researchers developed many Software Transactional Memories (STMs) with various APIs and semantics. However, reduced performance when exposed to high contention loads is still the major disadvantage of all the STMs. Designing a good transaction scheduling algorithm for a STM is challenging because it has to satisfy the three confronting requirements: (i) speed comparable with the speed of the simple Round Robin algorithm, (ii) good load balancing of processing units, and (iii) low contention among transactions. In this paper we developed the three transaction scheduling algorithms for the Python STM (PSTM), namely: (i) the Round Robin algorithm (RR), (ii) the Execution Time based Load Balancing algorithm (ETLB), and (iii) the Avoid Conflicts algorithm (AC) that uses information about tvariables used by individual transactions. Experimental results presented in this paper show that in the case of low contention and dual-core multicore, the RR's performance is worst, the ETLB's relative speedup over RR is 1.12 on average, and the AC's relative speedup over RR is 1.53 on average - from 1.12 in the worst case and up to 2.03 in the best case. Alternatively, experiments show that in the case of very short conflict-free transactions and in the case of high contention, all the three algorithms have comparable performance.

关键词： distributed systems parallel programming transactional memory execution time estimation transaction scheduling cloud computing

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A design of rural intelligent household micro-grid 2

A design of rural intelligent household micro-grid

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2nd international conference on Power and Renewable Energy, ICPRE 2017

作者： Tianzhu, Chen Linong, Wang Bin, Song Enwen, Li Siliang, Jian School of Electrical Engineering Wuhan University Wuhan China

ISBN: (纸本)9781538621561

Aiming at the reliability of power supply in China's rural areas and the poor quality of power, this paper designs a new household micro-id power supply system, which can widely absorb distributed energy, based on the characteristics of local distributed energy structure. Firstly, the distribution characteristics of the local renewable energy sources and load demand are accurately analyzed to determine the system structure and the capacity configuration of distributed generation. Then, analyze the spectrum of the output power of renewable energy. Based on the analysis, characteristics of energy storage unit and system constraints, determine the optimal capacity of energy storage unit. This system adopts hierarchical control mode, uses the upper scheduling control unit and a remote terminal to manage the whole system, and uses bi-directional inverter to made the micro-grid parallel in and cut smoothly. The design of the new rural household micro grid system is of great significance to the further development of micro-grid. © 2017 IEEE.

关键词： distributed power generation

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Improving MapReduce Performance with Progress and Feedback based Speculative Execution 2

Improving MapReduce Performance with Progress and Feedback b...

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2nd IEEE international conference on Smart cloud (Smartcloud)

作者： Ibrahim, Ibrahim Adel Bassiouni, Mostafa Univ Cent Florida Dept Elect & Comp Engn Orlando FL 32816 USA Univ Cent Florida Dept Comp Sci Orlando FL 32816 USA

ISBN: (纸本)9781538636848

Task stragglers dramatically impede parallel job execution of data-intensive computing in cloud Datacenters Due to the uneven distribution of input data resulted from heterogeneous data nodes, resource contention situations, and network configurations, it causes delay failures due to the violation of job completion time. However, data-intensive computing frameworks, such as MapReduce or Hadoop, employ a mechanism called speculative execution to deal with the straggler issue, speculative execution provide limited effectiveness because in many cases straggler identification occurs too late within a job lifecycle. Identifying the straggler and the timing of identifying it is very important for Straggler mitigation in Data-intensive cloud computing. Speculative execution method is a widely adopted as a straggler identification and mitigation scheme but it has certain inherent limitations. In this paper, we strive to make Hadoop more efficient in cloud environments. We present Progress and Feedback based Speculative Execution Algorithm (PFSE), a new Straggler identification scheme to identify the straggler MapReduce tasks based on the feedback information received from completed tasks beside the progress of the currently processing task, our extensive simulation shows that PFSE can outperform the dynamic scheduling techniques like Self-Learning MapReduce scheduler (SLM) and LATE. PFSE can assist in enhancing straggler Identification and mitigation for tolerating late-timing failures within data intensive cloud computing.

关键词： cloud computing MapReduce: Data-Intensive computing parallel and distributed Processing Straggler Identification Speculative Execution

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Demo abstract: Fog computing for improving user application interaction and context awareness 2

Demo abstract: Fog computing for improving user application ...

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2nd IEEE/ACM international conference on Internet-of-Things Design and Implementation, IoTDI 2017

作者： Saurez, Enrique Gupta, Harshit Ramachandran, Umakishore Mayer, Ruben Georgia Institute of Technology AtlantaGA United States Institute for Parallel and Distributed Systems University of Stuttgart Stuttgart Germany

ISBN: (纸本)9781450349666

Newgenerations of cloud applications are increasingly complex and pose lower latency requirements. The latter is forcing the industry to reduce network latency by adding computation nodes near the edge of the network, also known as Fog computing. To utilize the Fog nodes efficiently, the dynamic placement and migration of application components must be supported. To this end, a Fogaware application programming and deployment framework, called Foglets, has been proposed. This demonstration shows how the Foglets framework can be easily used to deploy applications in the Fog computing infrastructure: A video streaming application allows a moving user to continue watching a video on the closest available screen. © 2017 ACM.

关键词： Fog computing

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A Cost-effective Mobile Edge computing Model

A Cost-effective Mobile Edge Computing Model

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2018 2nd international conference on Economic Development and Education Management (ICEDEM 2018)

作者： Lin Qing Huang Yulei Intelligent Science and Information Engineering College Xi'an Peihua University Intelligent Science and Information Engineering College Xi’an Peihua University

With the explosive growth of smart devices and the advent of many new applications, data traffic over Internet has grown dramatically. Due to high latency and heavy burden on the backhaul links, traditional centralized network architecture cannot accommodate such challenges. Therefore, new architectures bring network functions to the edge of network, such as small-cell base stations and access point. Mobile Edge computing(MEC) has been recognized as a promising technique to provide caching, computation and communication functionalities at the edge of cellular networks. In this paper, we first give an overview of mobile edge networks, including architecture and features. Next, a distributed and local-first computing(DLFC) model based on MEC is proposed, including distributed computing model and transmission model. Subsequently, the comparison between DLFC and centralized cloud computing(CCC) model is given and analyzed service delay and performance. Finally, the conclusion of this paper and future direction is presented as well.

关键词： Mobile edge computing Mobile network Cost-effective Service latency

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Job starvation avoidance with alleviation of data skewness in Big Data infrastructure 2

Job starvation avoidance with alleviation of data skewness i...

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2nd international conference on computing and Communications Technologies, ICCCT 2017

作者： Subbiah, Sankari Mala, Sathya Nayagam, Senthil Department of Information Technology Sri Sai Ram Engineering College Chennai India STG InfoTech India LLP Chennai India

ISBN: (纸本)9781509062201

During the age of rush in the need for big data, Hadoop is a postulate or cloud-based platform that has been heavily encouraged for all solutions in the business world's big data problems. parallel execution of jobs consists of large data sets is done through map reduce in the hadoop cluster. The completion of job time will depend on the slowest running task in the job. The entire job is extended if one particular job takes longer time to finish and it is done by the delayer. An inequality in the measure of data allocated to each individual task is referred to as Data skewness. An efficient dynamic data splitting approach on Hadoop called the Hybrid scheduler who monitors the samples while running batch jobs and allocates resources to slaves depending on the complexity of data and the time taken for processing. In this paper, the effectiveness of web swarming is showcased using hadoop eliminating distributed Denial of Service (DDoS) attack detection scenarios in the Web servers. Query processing is done through Map Reduce in traditional Hadoop clusters and is replaced by the proposed Block chain query processing algorithm. Thereby improvise the execution time of the assigned task in the proposed system to mitigate the data skewness. The main aim of this paper is to avoid job starvation thus minimizing the response time efficiently during the process and mitigating data skewness in existing system. © 2017 IEEE.

关键词： Big data

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An Improved DNA Genetic Algorithm Based on Cell-like P System for Traveling Salesman Problem

An Improved DNA Genetic Algorithm Based on Cell-like P Syste...

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2018 2nd international conference on Computer Science and Intelligent Communication(CSIC 2018)

作者： Wenqian Zhang School of Business Shandong Normal University

Cell-like P systems are a class of distributed and parallel computing models. DNA genetic algorithms are evolutionary algorithm used for optimization purposes according to survival of the fittest idea, and DNA genetic algorithms are useful for NP-hard problems, especially the traveling salesman problem. Membrane computing(MC) combining with evolutionary computing(EC) is called evolutionary MC. This paper proposed an IDNA-DMS, which can not only easily get good approximation in time, but also converge rapidly. The experimental results show that the evolutionary MC algorithm IDNA-DMS can obtain more reliable optimization results with less iteration, which fully proves the effectiveness and efficiency of the algorithm.

关键词： DNA genetic algorithm membrane computing P system traveling salesman problem

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