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检索条件"任意字段=International Conference on Advances in Parallel and Distributed Computing"

共 24647 条记录，以下是4871-4880 订阅

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Optimal Noise Manipulation in Asymmetric Tournament 15th

Optimal Noise Manipulation in Asymmetric Tournament

引用

15th international conference on distributed computing and Artificial Intelligence, DCAI 2018

作者： Dong, Zhiqiang Luo, Zijun Key Lab for Behavioral Economic Science and Technology South China Normal University Guangzhou510006 China Department of Economics and International Business Sam Houston State University HuntsvilleTX77341-2118 United States

ISBN: (纸本)9783319996974

We fill a gap in the literature of asymmetric tournament by allowing the principal to optimally alter noise in relative performance evaluation, such that the observed performance of each agent is less or more dependent of ability and effort. We show that there exists an optimal noise level from the principal’s standpoint of expected profit maximization. It is shown that this optimal noise level is higher than what would induce the highest efforts from the two agents. © 2019, Springer Nature Switzerland AG.

关键词： Computer programming

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Copyright Certificate Storage and Trading System Based on Blockchain

引用

advances in Electrical Engineering and Computer Applications( AEECA), 2020 IEEE international conference on

作者： Pengbin Han Aina Sui Tao Jiang Chaonan Gu School of Computer Science and Cybersecurity Communication University of China Beijing China

ISBN: (数字)9781728165219

ISBN: (纸本)9781728165226

In the era of digitalization and networking, the high cost and long time of traditional centralized copyright protection methods make the copyright of digital works cannot be well protected and the infringement phenomenon be serious. Blockchain, as a decentralized distributed database, can store the copyright information of works. This paper researches and analyzes the advantages of blockchain in copyright protection and the current research status, and finally a copyright certificate storage and trading system based on blockchain is designed. In this system, registration confirmation, transaction certificate, and dispute protection are researched as a complete process. And the certificate storage data on the blockchain are precisely designed, which greatly reduces the time and cost of rights protection. What's more, the copyright of digital works is divided by studying laws related to copyright in China, which makes this system more suitable for practical applications.

关键词： Copyright protection Fabrics Contracts Organizations Peer-to-peer computing

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Towards Energy Efficiency and Power Trading Exploiting Renewable Energy in Cloud Data Centers

Towards Energy Efficiency and Power Trading Exploiting Renew...

引用

advances in the Emerging computing Technologies (AECT), international conference on

作者： Shahzad Aslam Sheraz Aslam Herodotos Herodotou Syed Muhammad Mohsin Khursheed Aurangzeb Department of Computer Science COMSATS University Islamabad Islamabad Pakistan Department of Electrical Engineering Cyprus University of Technology Limassol Cyprus Computer Engineering Department King Saud University Riyadh Saudi Arabia

ISBN: (数字)9781728144528

ISBN: (纸本)9781728144535

This study investigates the energy cost and carbon emission reduction problem in geographically distributed cloud data centers (DCs), where each DC is connected with its own renewable energy resources (RERs) for green energy generation. We consider four cloud DCs that are operated by a single cloud service provider. They consume energy from both RERs and from the commercial grid to meet the demand of cloud users. For energy pricing, we consider four different energy markets that offer varying energy prices per hour. Additionally, our proposed strategy enables DCs to sell excess electricity to the commercial grid in peak-price hours and purchase in low-cost hours according to power trading. This work also exploits energy storage devices (ESDs) to store energy for future use. We utilize real-time data requests, weather data, and pricing data for performing simulations and results affirm the effectiveness and productiveness of our proposed method to mitigate the energy cost and carbon emission of cloud DCs.

关键词： Cloud computing Task analysis Carbon dioxide Data centers Energy consumption Green products Renewable energy sources

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A Multimedia Platform for Mexican Cultural Heritage Diffusion 11th

A Multimedia Platform for Mexican Cultural Heritage Diffusio...

引用

11th international conference on Multimedia and Network Information Systems (MISSI)

作者： de Asis Lopez-Fuentes, Francisco Alejandro Ibanez-Ramirez, Juan Univ Autonoma Metropolitana Cuajimalpa Mexico City 04871 DF Mexico

ISBN: (纸本)9783319986784;9783319986777

New Web technologies that allow greater interaction among users have emerged in the Internet. In such a way that now it is common for users to participate actively by writing, publishing, exchanging or sharing digital content over the Internet. This fact has allowed the emergence of web communities, web services, social networking services, wikis, blogs, etc. that are developed on a specific topic. This paper presents a multimedia web platform for the creation, edition and dissemination of historical cultural contents. Security strategies are considered in the design and implementation of the interactive platform. A digital platform with this purpose is very important due to the great cultural heritage of Mexico. We evaluate the operation of our platform with cultural information related with different historic stages of Mexico such as prehispanic, colonial and independent. Our proposal seeks that the population has knowledge of cultural and historical contents in order to continuing preserve their cultural heritage.

关键词： distributed application Multimedia Internet Web 2.0

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Design-Space Exploration with Multi-Objective Resource-Aware Modulo Scheduling 25th

Design-Space Exploration with Multi-Objective Resource-Aware...

引用

25th international conference on parallel and distributed computing (Euro-Par)

作者： Oppermann, Julian Sittel, Patrick Kumm, Martin Reuter-Oppermann, Melanie Koch, Andreas Sinnen, Oliver Tech Univ Darmstadt Embedded Syst & Applicat Grp Darmstadt Germany Imperial Coll London Circuits & Syst Grp London England Univ Appl Sci Fulda Fac Appl Comp Sci Fulda Germany Karlsruhe Inst Technol Discrete Optimizat & Logist Grp Karlsruhe Germany Univ Auckland Parallel & Reconfigurable Comp Lab Auckland New Zealand

ISBN: (纸本)9783030294007;9783030293994

Many of today's applications in parallel and concurrent computing are deployed using reconfigurable hardware, in particular field-programmable gate arrays (FPGAs). Due to the complexity of modern applications and the wide spectsrum of possible implementations, manual design of modern custom hardware is not feasible. Computer-aided design tools enable the automated transformation of high-level descriptions into hardware. However, the efficient identification of Pareto-optimal solutions to trade-off between resource utilisation and throughput is still an open research topic. Combining resource allocation and modulo scheduling, we propose a new approach for design-space exploration of custom hardware implementations. Using problem-specific rules, we are able to exclude obviously dominated solutions from the design space before scheduling and synthesis. Compared to a standard, multi-criteria optimisation method, we show the benefits of our approach regarding runtime at the design level.

关键词： Reconfigurable hardware

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Online Fault Classification in HPC Systems Through Machine Learning 25th

Online Fault Classification in HPC Systems Through Machine L...

引用

25th international conference on parallel and distributed computing (Euro-Par)

作者： Netti, Alessio Kiziltan, Zeynep Babaoglu, Ozalp Sirbu, Alina Bartolini, Andrea Borghesi, Andrea Univ Bologna Dept Comp Sci & Engn Bologna Italy Leibniz Supercomp Ctr Garching Germany Univ Pisa Dept Comp Sci Pisa Italy Univ Bologna Dept Elect Elect & Informat Engn Bologna Italy

ISBN: (纸本)9783030294007;9783030293994

As High-Performance computing (HPC) systems strive towards the exascale goal, studies suggest that they will experience excessive failure rates. For this reason, detecting and classifying faults in HPC systems as they occur and initiating corrective actions before they can transform into failures will be essential for continued operation. In this paper, we propose a fault classification method for HPC systems based on machine learning that has been designed specifically to operate with live streamed data. We cast the problem and its solution within realistic operating constraints of online use. Our results show that almost perfect classification accuracy can be reached for different fault types with low computational overhead and minimal delay. We have based our study on a local dataset, which we make publicly available, that was acquired by injecting faults to an in-house experimental HPC system.

关键词： High-performance computing Exascale systems Resiliency Monitoring Fault detection Machine learning

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Optimizing the energy envelope in the Internet of Things using predictive cubic splines

Optimizing the energy envelope in the Internet of Things usi...

引用

Annual IEEE international conference on Sensing, Communication, and Networking Workshops (SECON Workshops)

作者： Saibal Ghosh Dharma P Agrawal Center for Distributed and Mobile Computing University of Cincinnati Cincinnati OH United States

ISBN: (数字)9781728110622

ISBN: (纸本)9781728110639

The paradigm of Internet of Things (IoT) is the result of rapid advances in the development of small low powered computing devices with wireless connectivity. This has given rise to a plethora of new applications, including, but not limited to monitoring, sensing, intrusion detection and others. Due to the nature of these applications, IoT devices are often burdened with receiving and transmitting a large volume of data that is time and delay sensitive. Furthermore, since most of these devices are battery powered, a data deluge often renders parts of the network depleted of energy, causing that part to go dark. In this work, we propose an energy optimization framework based on predictive cubic splines that anticipate a sudden increase in the bandwidth and minimize energy consumed by these devices while still maintaining an optimum degree of availability and reducing bottlenecks in the data flow.

关键词： Task analysis Delays Splines (mathematics) conferences Energy consumption Interpolation Character recognition

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Joint Service Placement and Computation Offloading in Mobile Edge computing: An Auction-based Approach

Joint Service Placement and Computation Offloading in Mobile...

引用

international conference on parallel and distributed Systems (ICPADS)

作者： Lei Zhang Zhihao Qu Baoliu Ye Bin Tang National Key Laboratory for Novel Software Technology Nanjing University Nanjing China Hohai University Nanjing China

ISBN: (数字)9781728190747

ISBN: (纸本)9781728183824

The emerging applications, e.g., virtual reality, online games, and Internet of Vehicles, have computation-intensive and latency-sensitive requirements. Mobile edge computing (MEC) is a powerful paradigm that significantly improves the quality of service (QoS) of these applications by offloading computation and deploying services at the network edge. Existing works on service placement in MEC usually ignore the impact of the different requirements of QoS among service providers (SPs), which is common in many applications such that online game requires extremely low latency and online video requires extremely large bandwidth. Considering the competitive relationship among SPs, we propose an auction-based resource allocation mechanism. We formulate the problem as a social welfare maximization problem to maximize effectiveness of allocated resources while maintaining economic robustness. According to our theoretical analysis, this problem is NP-hard, and thus it is practically impossible to derive the optimal solution. To tackle this, we design multiple rounds of iterative auctions mechanism (MRIAM), which divides resources into blocks and allocates them through multiple rounds of auctions. Finally, we conduct extensive experiments and demonstrate that our auction-based mechanism is effective in resource allocation and robust in economics.

关键词： Economics Solid modeling Quality of service Games Virtual reality Computational efficiency Resource management

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D2D-assisted computation offloading for mobile edge computing systems with energy harvesting 20

D2D-assisted computation offloading for mobile edge computin...

引用

20th international conference on parallel and distributed computing, Applications and Technologies, PDCAT 2019

作者： Li, Molin Chen, Tong Zeng, Jiaxin Zhou, Xiaobo Li, Keqiu Qi, Heng Tianjin Key Laboratory of Advanced Networking School of Computer Science and Technology College of Intelligence and Computing Tianjin University Tianjin300350 China School of Computer Science and Technology Dalian University of Technology Dalian116024 China

ISBN: (纸本)9781728126166

In mobile edge computing (MEC) systems with energy harvesting, the mobile devices are empowered with the energy that harvested from renewable energy sources. On the other hand, mobile devices can offload their computation-intensive tasks to the MEC server to further save energy and reduce the task execution latency. However, the energy harvested is unstable and the mobile devices have to make sure that the energy should not be run out. Moreover, the wireless channel condition between the mobile device and the MEC server is dynamically changing, leading to unstable communication delay. Considering the energy constraints and unstable communication delay, the benefit of computation offloading is limited. In this paper, we investigate D2D-assisted computation offloading for mobile edge computing systems with energy harvesting. In our method, the mobile device is allowed to offload its tasks to the MEC server with the help of its neighbor node. More Specifically, the neighbor node acts as a relay to help the mobile device to communicate with the MEC server. Our goal is to minimize the average task execution time by selecting an optimal execution strategy for each task, i.e., whether to execute the task locally, or offload it to the MEC server directly, or offload it to the MEC server with the help of the most suitable neighbor node, or just to drop it. We propose a low-complexity online algorithm, which stem from Lyapunov Optimization-based Dynamic Computation Offloading (LODCO) algorithm, to solve this problem. Extensive simulations verified the effectiveness of the proposed algorithm, where the average task execution time is reduced around 50% as compared to that of the original LODCO algorithm. © 2019 IEEE.

关键词： Energy harvesting

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A parallel Multi-keyword Top-k Search Scheme over Encrypted Cloud Data 16th

A Parallel Multi-keyword Top-k Search Scheme over Encrypted ...

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16th IFIP WG 10.3 international conference on Network and parallel computing, NPC 2019

作者： Yang, Maohu Dai, Hua Bao, Jingjing Yi, Xun Yang, Geng Nanjing University of Posts and Telecommunications Nanjing210023 China Jiangsu Security and Intelligent Processing Lab of Big Data Nanjing210023 China Royal Melbourne Institute of Technology University Melbourne3001 Australia

ISBN: (纸本)9783030307080

With searchable encryptions in the cloud computing, users can outsource their sensitive data in ciphertext to the cloud that provides efficient and privacy-preserving multi-keyword top-k searches. However, most existing top-k search schemes over encrypted cloud data are the centralize schemes which are limited in large scale data environment. To support scalable searches, we propose a parallel multi-keyword top-k search scheme over encrypted cloud data. In this scheme, the fragment-based encrypted inverted index is designed, which is indistinguishable and can be used for parallel searching. On the basis of such indexes, a Map-Reduce-based distributed computing framework is adopted to implement the parallel multi-keyword top-k search algorithms. Security analysis and experiment evaluation show that the proposed scheme is privacy-preserving, efficient and scalable. © 2019, IFIP international Federation for Information Processing.

关键词： Cloud computing

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