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Comparing performance of hierarchical identity-based signature schemes

Comparing performance of hierarchical identity-based signatu...

引用

作者： Chen, Peixin Wu, Yilun Su, Jinshu Wang, Xiaofeng College of Computer National University of Defense Technology Changsha410073 China National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha410073 China

The key escrow problem and high computational cost are the two major problems that hinder the wider adoption of hierarchical identity-based signature (HIBS) scheme. HIBS schemes with either escrow-free (EF) or online/offline (OO) model have been proved secure in our previous work. However, there is no much EF or OO scheme that has been evaluated experimentally. In this letter, several EF/OO HIBS schemes are considered. We study the algorithmic complexity of the schemes both theoretically and experimentally. Scheme performance and practicability of EF and OO models are discussed. © Copyright 2016 The Institute of Electronics, Information and Communication Engineers.

关键词： Computational complexity

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A novel L1 cache based on volatile STT-RAM 20th

A novel L1 cache based on volatile STT-RAM

引用

20th Annual Conference on Computer Engineering and Technology, NCCET 2016

作者： Hongguang, Zhang Minxuan, Zhang College of Computer National University of Defense Technology Changsha410073 China National Key Laboratory of Parallel and Distributed Processing National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789811031588

Spin-transfer torque random access memory (STT-RAM) is one of the most promising substitutes for universal main memory and cache due to its excellent scalability, high density and low leakage power. Nevertheless, the current non-volatile STT-RAM cache architecture also has some drawbacks, such as long write latency and high write energy, which limit the application of STTRAM in the top level cache design. To solve these problems, we relax the retention time of STT-RAM to explore its different write performance, and propose a novel STT-RAM L1 cache architecture implemented with volatile STT-RAM as well as its related refresh scheme. The performance of proposed design is the same as SRAM L1 cache while its overall power consumption is only 63.8% of the latter one. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Static random access storage

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Linearized alternating direction method of multipliers for constrained nonconvex regularized optimization 8

Linearized alternating direction method of multipliers for c...

引用

8th Asian Conference on Machine Learning, ACML 2016

作者： Qiao, Linbo Zhang, Bofeng Su, Jinshu Lu, Xicheng College of Computer National University of Defense Technology ChangSha410073 China National Laboratory for Parallel and Distributed Processing National University of Defense Tech-nology ChangSha410073 China

In this paper, we consider a wide class of constrained nonconvex regularized minimization problems, where the constraints are linearly constraints. It was reported in the litera- ture that nonconvex regularization usually yields a solution with more desirable sparse structural properties beyond convex ones. However, it is not easy to obtain the proximal mapping associated with nonconvex regularization, due to the imposed linearly constraints. In this paper, the optimization problem with linear constraints is solved by the Linearized Alternating Direction Method of Multipliers (LADMM). Moreover, we present a detailed convergence analysis of the LADMM algorithm for solving nonconvex compositely regular- ized optimization with a large class of nonconvex penalties. Experimental results on several real-world datasets validate the efficacy of the proposed algorithm. © 2016 L. Qiaoyz, B. Zhangy, J. Suyz & X. Luyz.

关键词： Constrained optimization

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Dolphin:A Search Engine for OSS Based on Crowd Discussions across Communities

Dolphin:A Search Engine for OSS Based on Crowd Discussions a...

引用

2016 IEEE 7th International Conference on Software Engineering and Service Science

作者： Yun Zhan Gang Yin Tao Wang Cheng Yang Zhixing Li Huaimin Wang National Laboratory for Parallel and Distributed Processing National University of Defense Technology

The global open source software resources have become an Internet-scale repository,which provide abundant resources for software ***,how to locate the desired resource efficiently and accurately from such large amounts is quite a challenge *** of recent works barely focus on the semantic similarity by analyzing the software itself,which often result in inappropriate *** this paper,we propose Dolphin,a global OSS search engine,which leverage the crowd discussions around OSS across communities for optimizing software *** employs the crowd wisdom as an important factor and combines it with the semantic similarity to optimize search results *** implement an OSS search engine based on the proposed approach,which provides online service *** experiments and user studies suggest the effectiveness of our approach.

关键词： Software retrieval ranking community influence

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Social Computing in Open Source Community:A Study of Software Reuse

Social Computing in Open Source Community:A Study of Softwar...

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The Second International Conference of Young Computer Scientists, Engineers and Educators,ICYCSEE 2016

作者： Mengwen Chen Tao Wang Cheng Yang Qiang Fan Gang Yin Huaimin Wang National Laboratory for Parallel and Distributed Processing National University of Defense Technology

Software projects are not developed in isolation but often build upon other open source resources. These projects form a kind of reference ecosystem regarded as a software world. Most of social computing works focus on social networks such as Facebook and weibo to mine information. However, few previous works analyze Open Source Community which could help developers conduct collaborative development. In this paper, we model the Java reference ecosystem as a network based on the reuse relationships of Git Hub-hosted Java projects and analyze the characteristics and the patterns of this reference ecosystem by using community detection and pattern discovery algorithms. Our study indicates that(1) Developers prefer to reuse software limited in only a small part of projects with cross cutting functionality or advanced applications.(2)Developers usually select software reused with similar function widely depending on different requirements, resulting to different patterns. Based on these collective intelligence, our study opens up several possible future directions of reuse recommendation, which are considered as guidance of collaborative development.

关键词： Social computing Open source software Reuse relationship Characteristic and pattern

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A validation of SonarQube issues related to real bugs based on open source software

A validation of SonarQube issues related to real bugs based ...

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2016联合国际信息技术、机械与电子工程国际会议

作者： Xiang Hou Yao Lu Yiang Gan Mengwen Chen Tao Wang Gang Yin National Laboratory for Parallel and Distributed Processing National University of Defense Technology

ISBN: (纸本)9781510830028

High reliability is an essential factor of modern software. At the same time, as software complexity is increasing day by day, bug counts and rate inevitably rises, leading to undermine software reliability. To avoid this problem, programmers always use issue-finding tools(bug detection) to discover the defects from source code in development of software. Recently, software inspection has been shown to be an effective way to speed up the process of source code verification and to move a portion of discovered defects from test to coding phase. As we know, modern software is often developed over many years. During this time, the commit metadata is becoming an important source of social characteristics. In this paper, our aim is to devise an empirical method to assess the percentage and the types of the issues found by issue finding tools are actual defects of the software.

关键词： Bug Detection Source Control System SonarQube Java Git

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ELM based Multiple Kernel k-means with Diversity-Induced Regularization

ELM based Multiple Kernel k-means with Diversity-Induced Reg...

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International Joint Conference on Neural Networks

作者： Yang Zhao Yong Dou Xinwang Liu Teng Li National University of Defense Technology National Laboratory for Parallel and Distributed Processing

ISBN: (纸本)9781509006212

Multiple-kernel k-means (MKKM) clustering has demonstrated good clustering performance by combining pre-specified kernels. In this paper, we argue that deep relationships within data and the complementary information among them can improve the performance of MKKM. To illustrate this idea, we propose a diversity-induced MKKM algorithm with extreme learning machine (ELM)-based feature extracting method. First, ELM, which has randomly chosen weights of hidden and output nodes, is applied to thoroughly extract features from data by generating different numbers of hidden nodes and using different functions. Second, an MKKM algorithm with diversity-induced regularization is utilized to explore the complementary information among kernels constructed from features. The problem could be solved efficiently by alternating optimization. Experimental results demonstrate that the proposed method outperforms state-of-the-art kernel methods.

关键词： Ecosystem models Elm Seeds Kernel output node Feature extraction Complementary Learning machines

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OpenMP 4.0 based heterogeneous parallel optimization of an engine combustion simulation application 2

OpenMP 4.0 based heterogeneous parallel optimization of an e...

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2nd IEEE International Conference on Computer and Communications, ICCC 2016

作者： Meifang, Yang Che, Yonggang Gao, Xiang Science and Technology on Parallel and Distributed Processing Laboratory China School of Computer China National University of Defense Technology Changsha China School of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9781467390262

LESAP is a combustion simulation application capable of simulating the chemical reactions and supersonic flows in the scramjet engines. It can be used to solve practical engineering problems and involves a large amount of computations. In this paper, we port and optimize LESAP with the OpenMP 4.0 accelerator model, targeting the heterogeneous many-core platform composed of general CPU and Intel Many Integrated Core (MIC). Based on the application characteristics, a series of techniques are proposed, including OpenMP 4.0 based task offloading, data movement optimization, grid-partition based load-balancing and SIMD optimization. The performance evaluation is done for a real combustion simulation configuration, with 532,0896 grid cells, on one Tianhe-2 supercomputer node. The results show that the resulting heterogenous code significantly outperforms the original CPU only code. When the heterogenous code runs on two Intel Xeon E5-2692 CPUs and three Intel Xeon Phi 31S1P coprocessors, it achieves a maximum speedup of 3.63x over the original code that only runs on the two Intel Xeon E5-2692 CPUs. © 2016 IEEE.

关键词： Program processors

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Learning from Wireless: a Prospective Approach to Human-Centered Computing

Learning from Wireless: a Prospective Approach to Human-Cent...

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International Joint Conference on Neural Networks

作者： Yong Lu Shaohe Lv Xue Yang Xiaodong Wang Minne Li Xingming Zhou Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology

ISBN: (纸本)9781509006212

One of the most important topics in Human-Centered Computing (HCC) is to recognise human's activities. In this paper, the technology of wireless-based activity recognition is introduced. By using wireless signals, one can achieve Non-Line-Of-Sight (NLOS) recognition without carrying any devices. Also, it is easy to deploy a wireless-based recognition system due to the ubiquity of wireless communication systems. The basic idea is to detect different characteristics of signal propagation that correspond to the distinct human behaviors. As a result, action recognition is performed by analyzing the distinguishable features of signal propagation. This paper introduces the basic principles and applications of wireless-based activity recognition, and discusses the challenges and related performance metrics. Finally, open problems are discussed to point out the future research trends.

关键词： Human-centered computing wireless Wireless communication systems Activity recognition recognition system Performance metrics signals Learning Paper Technology Human behavior

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DISVMs: Fast SVMs Training on Large-scale Data Sets

DISVMs: Fast SVMs Training on Large-scale Data Sets

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International Conference on Tools with Artificial Intelligence

作者： Lijuan Cui Changjian Wang Ziyang Li Yuxing Peng Science and Technology on Parallel and distributed Processing Laboratory National University of Defence Technology

ISBN: (纸本)9781509044603

Support Vector Machines (SVMs) are powerful classification tools. However, the model training is very time-consuming when meeting large scale data sets. Some efforts have been devoted to screening out non-support vectors (non-SVs) to accelerate the training. But their processes rely on prior knowledge of other classifiers with different parameters to screen out non-SVs. In this paper, we propose Directional Indicator Support Vector Machines (DISVMs) to efficiently identify non-SVs. DISVMs employs a directional indicator, which points to the approximately orthogonal direction of the separating hyperplane, to qualitatively define the location of different samples and thus identify non-SVs. Furthermore, DISVMs leverages a two-stage algorithm: the first stage is to compute the directional indicator. The second stage is to identify non-SVs using the indicator. To avoid misjudgement, we propose CnSV method for non-SVs based on the majority rule. DISVMs screens out non-SVs with light computation and little accuracy loss. Experiments show that our approach significantly reduces the total computation cost.

关键词： Support vector machines Non-support vector Directional indicator Computation efficiency Data preprocessing

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