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An Efficient Identity-Based Key Agreement Protocol in a Multiple PKG Environment

Wuhan University Journal of Natural sciences 2014年第5期19卷 455-460页

作者： ZHOU Huan WANG Xiaofeng SU Jinshu School of Computer National University of Defense Technology National Laboratory for Parallel and Distributed Processing National University of Defense Technology

Identity-based key agreement protocol affords a natural way to combine the participant＇s identity with its public key. However, most of them just consider the key agreement in a single private key generator （PKG） environment. In addition, the existing key agreement protocols have a great computing overhead for mobile computing which is more and more popular today. This paper proposes a new identity based key agreement protocol. With the help of mathematical tools, we make our protocol applied in multiple PKG environment. It also satisfies all the security properties which is set for key agreement protocol. Moreover, some of its time-consuming operations can be delivered to untrusted public computation resources, so its computing complexity can be greatly reduced.

关键词： key agreement identity based public computation multiple PKG environment

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Cooperative repair based on tree structure for multiple failures in distributed storage systems with regenerating codes 15

Cooperative repair based on tree structure for multiple fail...

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12th ACM International Conference on Computing Frontiers, CF 2015

作者： Pei, Xiaoqiang Wang, Yijie Ma, Xingkong Fu, Yongquan Xu, Fangliang Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha Hunan410073 China

ISBN: (纸本)9781450333580

Regenerating codes have been proposed to achieve an optimal trade-off curve between the amount of storage space and the network traffic for repair. However, existing repair schemes based on regenerating codes are inadequate to meet the requirements of small network traffic cost and high efficiency when repairing multiple failures. In this paper, we propose a cooperative repair scheme based on tree structure for multiple failures with regenerating codes, called CTREE. For generality, we propose a two-layer repair framework to support both repairs for single and multiple failures. For high repair efficiency, a parallel tree-structured data transmission technique is proposed to organize the data transmissions between the providers and newcomers. For small network network traffic cost, a core-based data exchange technique is proposed to organize the data exchanges between the coordinator and the other newcomers. To evaluate the performance of CTREE, we conduct experiments on both 30 physical and 200 virtual servers. Numerical analysis and extensive experiments confirm that CTREE can support both single and multiple failure repairs, significantly reduces the network traffic cost and improves the repair efficiency compared with the state-of-the-art approaches under various parameter settings. © Copyright 2015 ACM.

关键词： Repair

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DDPER: DECENTRALIZED distributed PRIORITIZED EXPERIENCE REPLAY

DDPER: DECENTRALIZED DISTRIBUTED PRIORITIZED EXPERIENCE REPL...

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2021 IEEE International Conference on Multimedia and Expo, ICME 2021

作者： Liu, Sidun Qiao, Peng Dou, Yong Li, Rongchun National Laboratory for Parallel and Distributed Processing National University of Defense Technology Hunan China

ISBN: (纸本)9781665438643

In off-policy reinforcement learning, prioritized experience replay plays an important role. However, the centralized prioritized experience replay becomes the bottleneck for efficient training. We propose to approximate the centralized prioritized experience replay in a distributed and decentralized way under certain mild assumptions. To be specific, each actor stores samples in its local replay in the same way as prioritized experience replay, the learner fetches a batch of samples from these replays following a certain strategy. We implement a Deep Q-Learning off-policy algorithm upon the proposed framework. The comparison experiments are performed on a commonly used subset of the Atari-57 learning environment. The experimental results show that the proposed framework speeds up training as the number of actors increases. With the same algorithm and hyper-parameter settings, the proposed framework with 16 actors achieves superior performance that Ape-X with 32 and even more actors does. © 2021 IEEE

关键词： Reinforcement learning

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Exploiting attribute redundancy in extracting open source forge websites

Exploiting attribute redundancy in extracting open source fo...

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4th International Conference on Cyber-Enabled distributed Computing and Knowledge Discovery, CyberC 2012

作者： Li, Xiang Zhu, Yanxu Yin, Gang Wang, Tao Wang, Huaimin National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)9780769548104

Open Source Forge (OSF) websites provide information on massive open source software projects, extracting these web data is important for open source research. Traditional extraction methods use string matching among pages to detect page template, which is time-consuming. A recent work published in VLDB exploits redundant entities among websites to detect web page coordinates of these entities. The experiment gives good results when these coordinates are used for extracting other entities of the target site. However, OSF websites have few redundant project entities. This paper proposes a modified version of that redundancy-based method tailored for OSF websites, which relies on a similar yet weaker presumption that entity attributes are redundant rather than whole entities. Like the previous work, we also construct a seed database to detect web page coordinates of the redundancies, but all at the attribute-level. In addition, we apply attribute name verification to reduce false positives during extraction. The experiment result indicates that our approach is competent in extracting OSF websites, in which scenario the previous method can not be applied. © 2012 IEEE.

关键词： Open source software

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Enhanced streamline texture synthesis for vector field visualization 4

Enhanced streamline texture synthesis for vector field visua...

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4th International Conference/Exhibition on High Performance Computing in the Asia-Pacific Region, HPC-Asia 2000

作者： Zhang, Wen Li, Xiaomei National Laboratory of Parallel and Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)0769505902

The Streamline Texture Synthesis (STS) method uses a different 1D texture to texture map each streamline and streamline textures are synthesized. The Enhanced STS (ESTS) adjusts the width of a streamline based on the critical point and maps several 1D textures to a streamline in order to accelerate computing. ESTS can also simulate animations and visualize 2D unsteady or 3D surface flows. The analyzed result proves that ESTS produces substantially better visual results and ESTS is fast enough to visualize vector field interactively. © 2000 IEEE.

关键词： Computer graphics

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Exploring the patterns of social behavior in Github 1

Exploring the patterns of social behavior in Github

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1st International Workshop on Crowd-Based Software Development Methods and Technologies, CrowdSoft 2014

作者： Yu, Yue Yin, Gang Wang, Huaimin Wang, Tao National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781450332248

Social coding paradigm is reshaping the distributed soft- ware development with a surprising speed in recent years. Github, a remarkable social coding community, attracts a huge number of developers in a short time. Various kinds of social networks are formed based on social activities among developers. Why this new paradigm can achieve such a great success in attracting external developers, and how they are connected in such a massive community, are interesting questions for revealing power of social coding paradigm. In this paper, we firstly compare the growth curves of project and user in GitHub with three traditional open source software communities to explore differences of their growth modes. We find an explosive growth of the users in GitHub and introduce the Diffusion of Innovation theory to illustrate intrinsic sociological basis of this phenomenon. Secondly, we construct follow-networks according to the follow behaviors among developers in GitHub. Finally, we present four typical social behavior patterns by mining follow-networks containing independence-pattern, group-pattern, star-pattern and hub-pattern. This study can provide several instructions of crowd collaboration to newcomers. According to the typical behavior patterns, the community manager could design corresponding assistive tools for developers. Copyright 2014 ACM.

关键词： Software design

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Performance evaluation of data value prediction schemes

Performance evaluation of data value prediction schemes

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作者： Xiao, Yong Zhou, Xing-Ming National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China Chinese Academy of Science

Data value prediction has been widely accepted as an effective mechanism to break data hazards for high performance processor design. Several works have reported promising performance potential. However, there is hardly enough information that is presented in a clear way about performance comparison of these prediction mechanisms. This paper investigates the performance impact of four previously proposed value predictors, namely last value predictor, stride value predictor, two-level value predictor and hybrid (stride+two-level) predictor. The impact of misprediction penalty, which has been frequently ignored, is discussed in detail. Several other implementation issues, including instruction window size, issue width and branch predictor are also addressed and simulated. Simulation results indicate that data value predictors act differently under different configurations. In some cases, simpler schemes may be more beneficial than complicated ones. In some particular cases, value prediction may have negative impact on performance. © 2005 Springer science + Business Media, Inc.

关键词： Data processing

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parallel pipeline implementation for moving objects detection in traffic video analysis on a heterogeneous platform 4th

Parallel pipeline implementation for moving objects detectio...

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4th International Conference on Computer Engineering and Networks, CENet2014

作者： Li, Teng Dou, Yong Jiang, Jingfei Qiao, Peng Department of Computer Science National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha410073 China

ISBN: (纸本)9783319111032

Moving objects detection is important in traffic video analysis, and many algorithms are being increasingly applied to moving objects detection. Most of these algorithms are time-consuming and cannot satisfy real-time demand in traffic video analysis by using a conventional central processing unit (CPU) sequential method. The emergence of the graphics processing unit (GPU) and multi-core CPU provides a method to accelerate the aforementioned algorithms to meet demand. In this study, we provide a GPU-accelerated implementation of the background subtraction algorithm and the morphological operation algorithm. Then, the connected component labeling algorithm is parallelized on a multi-core CPU with Open Multi-processing (OpenMP). Furthermore, parallel pipeline implementation on a heterogeneous platform is proposed by integrating the aforementioned algorithms. Experimental results show that the proposed implementation achieves a significant speedup of up to 5×, compared with sequential implementation on a CPU. © Springer International Publishing Switzerland 2015.

关键词： Program processors

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Deadline-oriented task scheduling for mapreduce environments 15th

Deadline-oriented task scheduling for mapreduce environments

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15th International Conference on Algorithms and Architectures for parallel processing, ICA3PP 2015

作者： Hu, Minghao Wang, Changjian You, Pengfei Huang, Zhen Peng, Yuxing National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha410072 China

ISBN: (纸本)9783319271217

To provide timely results for ‘Big Data Analytics’, it is crucial to satisfy deadline requirements for MapReduce jobs in production environments. In this paper, we propose a deadline-oriented task scheduling approach, named Dart, to meet the given deadline and maximize the input size if only part of the dataset can be processed before the time limit. Dart uses an iterative estimation method which is based on both historical data and job running status to precisely estimate the realtime job completion time. By comparing the estimated time with the deadline constraint, a YARN-based task scheduler dynamically decides whether continuing or terminating the map *** have validated our approach using workloads from OpenCloud and Facebook on a cluster of 60 virtual machines. The results show that Dart can not only effectively meet the deadline but also process near-maximal data volumes even when the deadline is set to be extremely small and limited resources are allocated. © Springer International Publishing Switzerland 2015.

关键词： MapReduce

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Mining and recommending software features across multiple web repositories 13

Mining and recommending software features across multiple we...

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5th Asia-Pacific Symposium on Internetware, Internetware 2013

作者： Yu, Yue Wang, Huaimin Yin, Gang Liu, Bo School of Computer Science National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China

ISBN: (纸本)9781450323697

The Internetware" paradigm is fundamentally changing the traditional way of software development. More and more software projects are developed, maintained and shared on the Internet. However, a large quantity of heterogeneous software resources have not been organized in a reasonable and efficient way. Software feature is an ideal material to characterize software resources. The effectiveness of feature- related tasks will be greatly improved, if a multi-grained feature repository is available. In this paper, we propose a novel approach for organizing, analyzing and recommend- ing software features. Firstly, we construct a Hierarchical rEpository of Software feAture (HESA). Then, we mine the hidden affnities among the features and recommend relevant and high-quality features to stakeholders based on HESA. Finally, we conduct a user study to evaluate our approach quantitatively. The results show that HESA can organize software features in a more reasonable way compared to the traditional and the state-of-the-art approaches. The result of feature recommendation is effective and interesting. Categories and Subject Descriptors D.2.9 [Software Engineering]: Mining Software Reposi- tory;H.3.3 [Information Storage and retrieval]: Fea- ture Model, Clustering, Query formulation General Terms Algorithms, Human Factors.

关键词： Software design

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