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

共 1761 条记录，以下是1631-1640 订阅

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the Library for Hadoop Deflate Compression Based on FPGA Accelerator with Load Balance

The Library for Hadoop Deflate Compression Based on FPGA Acc...

引用

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

作者： Haixin Du Jiankui Zhang Shihao Sha Cai Ye Qiuming Luo College of Computer Science and Software Engineering Shenzhen University NHPCC/Guangdong Key Laboratory of popular HPC and Guangdong Province Engineering Center of China-made High Performance Data Computing System Shenzhen China

ISBN: (数字)9781728126166

ISBN: (纸本)9781728126173

Hadoop application will produce lots of intermediate results in the map/reduce process that requires disk I/O and network transmission. By compressing the large-scale data of intermediate result, it will greatly improve disk access efficiently and reduce program run time. Hardware-accelerated solutions have become more desirable. this paper design a multi-FPGA compression accelerator on the Hadoop platform, and the system performance analysis compared with a software-only solution that mainly uses CPU to processing. the testing programs are zpipe, TestDFSIO and Terasort. In contrast with the software-only solution. the max speedup of zpipe is 6.55X (single FPGA) and 10.24X (dual FPGA), the max speedup of TestDFSIO is 6.28X (single FPGA) and 6.28X (dual FPGA), and the max speedup of Terasort application is up to 3.25X(single FPGA) and 3.35X(dual FPGA).

关键词： Handheld computers conferences Computer science Software engineering distributed databases Indexes

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Market-Oriented Grid computing and the Gridbus Middleware

Market-Oriented Grid Computing and the Gridbus Middleware

引用

international conference on Advanced computing and Communications (ADCOM)

作者： Rajkumar Buyya Grid Computing and Distributed Systems (GRIDS) Laboratory University of Melbourne Australia

Grid computing, one of the latest buzzwords in the ICT industry, is emerging as a new paradigm for Internet-based parallel and distributing computing. Despite a number of advances in grid computing, resource management and application scheduling in such environments continues to be a challenging and complex undertaking. this is due to geographic distribution of grid resources owned by different organizations with different usage policies, cost models and varying load and availability patterns with time. this tutorial introduces fundamental principles of grid computing and computational economy and discusses how they impact on emerging computational and data grid technologies. It identifies resource management challenges and introduces new challenges and requirements introduced by the grid economy on grid service providers (GSPs) and grid service consumers. the tutorial presents a service-oriented grid architecture inspired by computational economies and demonstrates how it can be realized by leveraging the existing grid technologies and building new economic-oriented capabilities and components. We present solutions to these challenges based on our experience in designing and developing market-oriented Gridbus technologies such as Grid Market Directory, Grid Bank, Grid Service Broker, Workflow Engine, and SLA-based enterprise Grid Resource Allocation system. Case studies on the use of Gridbus middleware in the creation of various e-science and e-business applications and their deployment on national/international utility-oriented grids along with its impact on emerging cloud computing paradigm will also be highlighted.

关键词： Grid computing Middleware Resource management Computer industry Internet Concurrent computing distributed computing Job shop scheduling Processor scheduling Costs

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Robustness in context-aware mobile computing

Robustness in context-aware mobile computing

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IEEE international conference on Wireless and Mobile computing, Networking And Communications (WiMob)

作者： Hannes Wolf Klaus Herrmann Kurt Rothermel Institute of Parallel and Distributed Systems Universität Stuttgart Germany

High level context recognition and situation detection are enabling technologies for unobtrusive mobile computing systems. Significant progress has been made in processing and managing context information, leading to sophisticated frameworks, middlewares, and algorithms. Despite great improvements, context aware systems still require a significantly increased recognition accuracy for high-level context information on uncertain sensor data to enable the robust execution of context-aware applications. Recently Adaptable Pervasive Workflows (APF)s have been presented as innovative programming paradigm for mobile context-aware applications. We propose a novel Flow Context System (FlowCon) that builds upon APFs. FlowCon uses structural information from the APF to increase accuracy of uncertain high-level context information up to 49%. this way we make an important step to enable robust execution of mobile context-aware applications.

关键词： Context Blood Accuracy Uncertainty Semantics Mobile communication

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TOTEM : Token for controlled computation: Integrating Blockchain with Big Data

TOTEM : Token for controlled computation: Integrating Blockc...

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international conference on computing and Networking Technology (ICCNT)

作者： Dhanya therese Jose Antorweep Chakravorty Chunming Rong University of Stavanger Stavanger Norway

Conventional methods for data analysis demands data be moved across networks for analysis. Along with it being highly network intensive, data owners are also reluctant to provide their data due to security and privacy breaches. In order to overcome these issues, we proposed TOTEM: Token for controlled computation, that combines both blockchain technologies and big data systems. the objective is to allow computation to be taken to the data, rather than moving the data to the computation. A third-party user uses the TOTEM SDK to create a MapReduce code for computation, which will be executed within the data owner's environment. this computational system prevents the execution of any malicious functions in the user code, by putting constraints on computational operations. A pre-defined totem will be assigned to authorised users, based on their computational needs. A smart contract performs pre-checks on user-submitted code and associated totem value, by using a totem estimator to determine the required totem for executing the given code. A Totem manager and updater is introduced to coordinate computation of user code until it exits gracefully, or the assigned totem gets exhausted. the TOTEM project ensures data security by allowing organisations to open their data centers and allow disruptive business models.

关键词： Blockchain Big Data Smart contracts distributed ledger Computer architecture Peer-to-peer computing Security

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GPU parallel Acceleration of Frequency Domain Algorithm for Calculating Radar Target Echoes

GPU Parallel Acceleration of Frequency Domain Algorithm for ...

引用

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

作者： Zhao Naixuan Zhang Ge Wang Zijian Kuang Ling University of Electronic Science and Technology of China

ISBN: (数字)9781728126166

ISBN: (纸本)9781728126173

After the radar detects the target by transmitting signal, the target returns echo signal, which contains the position and velocity of the target. To meet the demand of high-performance echo computing for real-time radar simulation, this paper proposes a frequency domain algorithm for calculating echoes based on GPU. the experiments are conducted to compare the execution time on CPU and GPU. Moreover, we do a lot of tests to contrast the traditional GPU acceleration time domain algorithm and the algorithm proposed in this paper. the results show that, compared with the traditional CPU-based simulator, the GPU-based simulator calculates the echo faster. And with the increase of the number of sampling points, speedup ratio rises. Compared with the existing GPU acceleration time domain algorithm, the GPU-based frequency domain algorithm for calculating echo improves the real-time performance, and with the increase of the number of the targets in the scene, the acceleration ratio promotes obviously. Furthermore, the phase offset due to the time delay is performed in the frequency domain directly, which improve the ranging accuracy.

关键词： Graphics processing units Frequency-domain analysis Radar Time-domain analysis Delay effects Radar antennas Acceleration

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Exploring the Emerging technologies Within the Blockchain Landscape 6th

Exploring the Emerging Technologies Within the Blockchain La...

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6th international conference on Emerging technologies in computing, iCETiC 2023

作者： Tareq, Mohammad Ali Tripathi, Piyush Issa, Nurhayati Md. Miraz, Mahdi H. Kuala Lumpur Malaysia Texas A&M University College Station College StationTX United States Yamaguchi University Yamaguchi Japan Xiamen University Malaysia Selangor Malaysia Wrexham University Wrexham United Kingdom University of South Wales Pontypridd United Kingdom

ISBN: (纸本)9783031502149

Although blockchain technology was first introduced in 2008 and materialised in 2009, the early usage of blockchain were mainly limited to financial technologies, particularly cryptocurrencies. Later, blockchain became a widespread emerging technology, utilised in multifaceted sectors and applications. In fact, various new and innovative application of blockchain and distributed ledger technologies are still continuously being researched and explored. On the other hand, smart-contracts were first introduced in 1990s, however, it did not gain enough popularity until being integrated with blockchain technologies lately. the duo lately been seen as the key to many innovations in various industries and sectors. So, we took data from 1445 blockchain-related patent documents and tried to map out the historical and current trends in patenting activities in the blockchain field. this helps us get a better grasp of how blockchain technologies are evolving and being tracked. In addition to serving as an indicator of science and technology growth, patents are also used to judge the research potential and development of a particular technology. © 2024, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Smart contract

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Reusable software components for performability tools, and their utilization for web-based configurable tools 10th

Reusable software components for performability tools, and t...

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10th international conference on Modelling Techniques and Tools for Computer Performance Evaluation, Tools 1998

作者： Van Moorsel, Aad P. A. Huang, Yiqing Distributed Software Research Department Bell Laboratories Research Lucent Technologies 600 Mountain Ave Murray HillNJ07974 United States Center for Reliable and High-Performance Computing Coordinated Science Laboratory University of Illinois at Urbana-Champaign 1308 W. Main St UrbanaIL61801 United States

ISBN: (纸本)3540649492

this paper discusses software reusability strategies for performance and reliability modeling tools. Special emphasis is on web-embedded tools, and the potential interaction between such tools. We present the system analysis tools (SAT) application programming interface, which allows for quickly embedding existing tools in the web, and generally simplifies programming analysis tools by structured reuse. We also introduce the FREUD project, which has as primary aim to establish a single point of access to a variety of web-enabled tools. In addition, FREUD facilitates configurable web tools by allowing a user to select from the registered modeling formalisms, solvers and graphics tools, and by providing glue between the tools through scripting. We will argue that this form of reuse is particularly suitable for performability modeling tools because of their predictable usage pattern. © Springer-Verlag Berlin Heidelberg 1998.

关键词： Computer software reusability

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Detecting Model Changes in Organisational Processes: A Cloud-Based Approach 10th

Detecting Model Changes in Organisational Processes: A Clou...

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10th IFIP WG 6.12 European conference on Service-Oriented and Cloud computing, ESOCC 2023

作者： Fabra, J. Gallego-Fontenla, V. Vidal, J.C. de Quirós, J. García Álvarez, P. Lama, M. Bugarín, A. Ramos-Soto, A. University of Zaragoza Zaragoza Spain Research Center in Intelligent Technologies University of Santiago de Compostela A Coruña Spain Inverbis Analytics Lugo Spain

ISBN: (纸本)9783031462344

Process mining techniques extract knowledge from event logs within organizations to understand and improve the behavior of their business processes. these techniques utilize a wide range of methods to automatically generate process models from event log data, simplify these models, calculate various indicators to optimize performance, and visualize and explain model behavior. However, these techniques often treat process models as static entities, despite the inherent dynamic nature of processes. Commercial platforms frequently lack the ability to detect and describe changes (also known as concept drift) in the models, which can impact the conclusions and results derived from process mining. this paper presents the INSIDE-TUTTO project, which has developed a concept drift detection algorithm for application in business organizations and transition to the commercial market through Inverbis Analytics. the original algorithm was not designed to operate in real-world scenarios with large volumes of data. By combining distributed architectures and the cloud computing paradigm, the algorithm was evolved into a commercial version deployed within Inverbis Analytics’ Azure-based technological infrastructure. © IFIP international Federation for Information Processing 2023.

关键词： Data mining

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Comparative Analysis of Security Algorithms used in Cloud computing

Comparative Analysis of Security Algorithms used in Cloud Co...

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international conference on computing for Sustainable Global Development (INDIACom)

作者： Mohd Tajammul Rafat Parveen Iftikhar Aslam Tayubi Jamia Millia Islamia New Delhi India King Abdulaziz University Jeddah Saudi Arabia

Cloud computing is a technique that enables the users to access applications to infrastructure through subscription methods on remote location. Cloud computing, being collective technique, possesses features of various technologies like Virtual Private Network (VPN), distributed technology, parallel computing, grid computing as well as ubiquitous computing. Cloud storage is the infrastructure offered by the cloud computing in order to facilitate users to upload and access their data on cloud space. Due to multitenancy of cloud storage, the data uploaded on it is the more prone to security breaches. To secure the data on cloud, cryptographic technique is used which works like safeguard against data leakage. this research work focuses on cryptographic algorithms from most basic to advance and also presents their comparative analysis. Moreover, the paper focuses on the nature of the algorithms in context of cloud that is homogeneous and heterogeneous nature. In the cloud computing, homogeneous nature algorithm is used only if the encryptors and decryptors both are same while heterogeneous refers to the situation in which encryptors and decryptors are different entities.

关键词： Cloud computing parallel processing Ubiquitous computing Grid computing Virtual private networks Cryptography

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Quantifying the Impact of Design Strategies for Big Data Cyber Security Analytics: An Empirical Investigation

Quantifying the Impact of Design Strategies for Big Data Cyb...

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

作者： Faheem Ullah M. Ali Babar CREST ??? Centre for Research on Engineering of Software Technologies The University of Adelaide Australia Cyber Security Adelaide The University of Adelaide Australia

ISBN: (数字)9781728126166

ISBN: (纸本)9781728126173

Big Data Cyber Security Analytics (BDCA) systems use big data technologies (e.g., Hadoop and Spark) for collecting, storing, and analyzing a large volume of security event data to detect cyber-attacks. the state-of-the-art uses various design strategies (e.g., feature selection and alert ranking) to help BDCA systems to achieve the desired levels of accuracy and response time. However, the use of these strategies in the state-of-the-art is not consistent, which exposes a lack of consensus on "when to use (and not to use) these design strategies?" In this paper, we follow a systematic experimentation framework to quantify the impact of four design strategies on the accuracy and response time with respect to three contextual factors i.e., security data, machine learning model employed in the system, and the execution mode of the system. For the aimed quantification, we performed experiments on a Hadoop-based BDCA system using four security datasets, five machine learning models, and three execution modes. Our findings lead us to formulate a set of design guidelines that will help researchers and practitioners to decide when to use (and not to use) the design strategies.

关键词： Time factors Feature extraction distributed databases Training Big Data Computer security

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