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28th International Conference on Software Engineering and Knowledge Engineering, SEKE 2016

作者： Song, Chenxi Wang, Tao Yin, Gang Zhang, Xunhui Yang, Cheng National Laboratory for Parallel and Distributed Processing College of Computer National University of Defense Technology Changsha China

ISBN: (纸本)189170639X

With the rapid development of open source software, various elements such as OSS, developers, users and online posts, across different communities and their interactions constitute a novel software ecosystem. Most of the current researches about software ecosystems care the connections between software, and few of them consider the relationship across communities from an overall perspective, and fail to cover the users and their activities which should be an indispensable part of the OSS ecosystem. This paper model the OSS ecosystem as a graph, which combines different types of OSS communities as a whole. Based on this graph model, we analyze the characteristics of ecosystem, like the evolution, competition and symbiosis. In addition, we build a recommendation system as well, and the experiment results suggest the validation of our approach. Copyright © 2016 by KSI Research Inc. and Knowledge Systems Institute Graduate School.

关键词： Ecosystems

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Large-scale virtual machines provisioning in clouds： challenges and approaches

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Frontiers of Computer Science 2016年第1期10卷 2-18页

作者： Zhaoning ZHANG Dongsheng LI Kui WU National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha 410073 China Computer Science Department University of Victoria Victoria V8W 2Y2 Canada

The scale of global data center market has been explosive in recent years. As the market grows, the demand for fast provisioning of the virtual resources to support elas- tic, manageable, and economical computing over the cloud becomes high. Fast provisioning of large-scale virtual ma- chines （VMs）, in particular, is critical to guarantee quality of service （QoS）. In this paper, we systematically review the existing VM provisioning schemes and classify them in three main categories. We discuss the features and research status of each category, and introduce two recent solutions, VMThunder and VMThunder＋, both of which can provision hundreds of VMs in seconds.

关键词： cloud computing IaaS large scale virtual ma-chine provisioning

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Learning non-local image diffusion for image denoising

arXiv

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arXiv 2017年

作者： Qiao, Peng Dou, Yong Feng, Wensen Chen, Yunjin National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha410073 China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing

Image diffusion plays a fundamental role for the task of image denoising. Recently proposed trainable nonlinear reaction diffusion (TNRD) model defines a simple but very effective framework for image denoising. However, as the TNRD model is a local model, the diffusion behavior of which is purely controlled by information of local patches, it is prone to create artifacts in the homogenous regions and over-smooth highly textured regions, especially in the case of strong noise levels. Meanwhile, it is widely known that the non-local selfsimilarity (NSS) prior stands as an effective image prior for image denoising, which has been widely exploited in many nonlocal methods. In this work, we are highly motivated to embed the NSS prior into the TNRD model to tackle its weaknesses. In order to preserve the expected property that end-to-end training is available, we exploit the NSS prior by a set of non-local filters, and derive our proposed trainable non-local reaction diffusion (TNLRD) model for image denoising. Together with the local filters and influence functions, the non-local filters are learned by employing loss-specific training. The experimental results show that the trained TNLRD model produces visually plausible recovered images with more textures and less artifacts, compared to its local versions. Moreover, the trained TNLRD model can achieve strongly competitive performance to recent state-of-theart image denoising methods in terms of peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). Copyright © 2017, The Authors. All rights reserved.

关键词： Image denoising

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Pegasus：a distributed and load-balancing fingerprint identification system

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Frontiers of Information Technology & Electronic Engineering 2016年第8期17卷 766-780页

作者： Yun-xiang ZHAO Wan-xin ZHANG Dong-sheng LI Zhen HUANG Min-ne LI Xi-cheng LU National Laboratory for Parallel and Distributed Processing College of Computer National University of Defense Technology Changsha 410003 China

Fingerprint has been widely used in a variety of biometric identification systems in the past several years due to its uniqueness and immutability. With the rapid development of fingerprint identification techniques, many fingerprint identification systems are in urgent need to deal with large-scale fingerprint storage and high concurrent recognition queries, which bring huge challenges to the system. In this circumstance, we design and implement a distributed and load-balancing fingerprint identification system named Pegasus, which includes a distributed feature extraction subsystem and a distributed feature storage subsystem. The feature extraction procedure combines the Hadoop Image processing Interface（HIPI） library to enhance its overall processing speed; the feature storage subsystem optimizes MongoD B＇s default load balance strategy to improve the efficiency and robustness of *** and simulations are carried out, and results show that Pegasus can reduce the time cost by 70% during the feature extraction procedure. Pegasus also balances the difference of access load among front-end mongos nodes to less than 5%. Additionally, Pegasus reduces over 40% of data migration among back-end data shards to obtain a more reasonable data distribution based on the operation load（insertion, deletion, update, and query） of each shard.

关键词： distributed fingerprint identification distributed MongoD B Load balancing

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False-positive probability and compression optimization for tree-structured bloom filters

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ACM Transactions on Modeling and Performance Evaluation of Computing Systems 2016年第4期1卷 1–39页

作者： Fu, Yongquan Biersack, Ernst National Key Laboratory for Parallel and Distributed Processing College of Computer Science National University of Defense Technology Sanyi Road Changsha Hunan Province410073 China CAIPY Valbonne06560 France

Bloom filters are frequently used to to check the membership of an item in a set. However, Bloom filters face a dilemma: the transmission bandwidth and the accuracy cannot be optimized simultaneously. This dilemma is particularly severe for transmitting Bloom filters to remote nodes when the network bandwidth is limited. We propose a novel Bloom filter called BloomTree that consists of a tree-structured organization of smaller Bloom filters, each using a set of independent hash functions. BloomTree spreads items across levels that are compressed to reduce the transmission bandwidth need. We show how to find optimal configurations for BloomTree and investigate in detail by how much BloomTree outperforms the standard Bloom filter or the compressed Bloom filter. Finally, we use the intersection of BloomTrees to predict the set intersection, decreasing the false-positive probabilities by several orders of magnitude compared to both the compressed Bloom filter and the standard Bloom filter. © 2016 ACM 2376-3639/2016/09-ART19 $15.00

关键词： Genetic algorithms

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An Efficient Label Routing on High-Radix Interconnection Networks

An Efficient Label Routing on High-Radix Interconnection Net...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Fei Lei Dezun Dong Xiangke Liao College of Computer National University of Defense Technology China National Laboratory for Parallel and Distributed Processing National University of Defense Technology China Collaborative Innovation Center of High Performance Computing National University of Defense Technology China

ISBN: (纸本)9781538632086

Cost-effective adaptive routing has a significant impact on overall performance for high-radix hierarchical topologies, such as Dragonfly, which achieve a lower network diameter than traditional topologies, Torus and Fat tree, but exhibit a lower degree of adaptiveness for shortest-path rout- ing. Existing adaptive routing methods for those hierarchical topologies improve the adaptiveness by increasing path length, i.e. local or global adaptive routing, and thus suffer from complex and costly deadlock avoidance. This work aims to maximize the routing adaptiveness at the minimum cost of deadlock avoidance. We propose a label routing method for high-radix hierarchical networks. This label routing utilizes a co-design methodology and coordinates the two pipelines, input queue and routing computation, in the router microarchitec- ture. Packets in the input buffer are labeled by our routing algorithm depending on network states. We reorganize the input buffer and develop a label routing algorithm, named Green-Red Routing, GRR. GRR relaxes the requirement of using virtual channels to eliminate routing deadlock, and mitigates buffer resources dedicated to deadlock avoidance. GRR manages the buffer resources and balance its utilization elaborately, and achieve fully adaptive routing efficiently. We conduct extensive experiments to evaluate the performance of GRR on Dragonfly and compare it with state-of-the-art works. The results show that GRR achieves 10%-35% higher performance than existing routing algorithms under most traffic patterns.

关键词： Routing System recovery Network topology Topology Resource management Adaptive systems Organizations

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An improved algorithm for reconstructing singular connection in the multi-block cfd applications

arXiv

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arXiv 2017年

作者： Yong-Xian, Wang Li-Lun, Zhang Yong-Gang, Che Chuan-Fu, Xu Wei, Liu Hua-Yong, Liu Zheng-Hua, Wang College of Computer National University of Defense Technology Changsha410073 China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha410073 China State Key Laboratory of Aerodynamics Mianyang621000 China

In this paper, an improved algorithm is proposed for the reconstruction of singularity connectivity from the available pairwise connections during preprocessing phase. To evaluate the performance of our algorithm, an in-house CFD code, in which high-order finite-difference method for spatial discretization, running on the Tianhe-1A supercomputer is employed. Test cases with a varied amount of mesh points are chosen, and the test results indicate that the improved singular connection reconstruction algorithm can achieve a 2000× speedup at least compared with the naive search method adopt in the former version of our code. Moreover, the parallel efficiency can be benefited from the strategy of local communication based on the new algorithm. Copyright © 2017, The Authors. All rights reserved.

关键词： Finite difference method

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A distributed Relation Detection Approach in the Internet of Things

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Mobile Information Systems 2017年第1期2017卷

作者： Zhu, Weiping Lu, Hongliang Cui, Xiaohui Cao, Jiannong International School of Software Wuhan University Wuhan China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China Department of Computing Hong Kong Polytechnic University Kowloon Hong Kong

In the Internet of Things, it is important to detect the various relations among objects for mining useful knowledge. Existing works on relation detection are based on centralized processing, which is not suitable for the Internet of Things owing to the unavailability of a server, one-point failure, computation bottleneck, and moving of objects. In this paper, we propose a distributed approach to detect relations among objects. We first build a system model for this problem that supports generic forms of relations and both physical time and logical time. Based on this, we design the distributed Relation Detection Approach (DRDA), which utilizes a distributed spanning tree to detect relations using in-network processing. DRDA can coordinate the distributed tree-building process of objects and automatically change the depth of the routing tree to a proper value. Optimization among multiple relation detection tasks is also considered. Extensive simulations were performed and the results show that the proposed approach outperforms existing approaches in terms of the energy consumption. © 2017 Weiping Zhu et al.

关键词： Internet of things

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An Energy Efficient Optimized Control Algorithm for Urban Rail Transit System 35

An Energy Efficient Optimized Control Algorithm for Urban Ra...

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第35届中国控制会议

作者： ZHANG Hongguang SONG Mengxiao ZHANG Minxuan College of Computer National University of Defense Technology College of Mechatronic Engineering and Automation National University of Defense Technology National Laboratory for Parallel and Distributed Processing National University of Defense Technology

ISBN: (纸本)9781509009107

The energy consumption of urban rail transit system involves train traction, air conditioning system, elevator, water supply and drainage equipment and so on, wherein the traction energy consumption accounts for more than 40% of the total energy consumption. With more concerning about low-carbon and environment protection, it has become a research hotspot that how to minimize the traction energy consumption during operation. Aiming at the optimized control of single train in complex line conditions, we design an algorithm based on recursion, by which we can obtain the most efficient control strategy with a set of constraints and effectively reduce the traction energy consumption. Meanwhile, we focus on the multiple-unit trains' cooperative control issue, and give the relevant solutions to improve the proportion of recovered renewable braking energy.

关键词： urban rail transit efficient algorithm recursion cooperative control

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SinglA image super-resolution via classified sparse Representation 13

SinglA image super-resolution via classified sparse Represen...

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13th International Conference on Embedded Software and System, ICESS 2016

作者： Lai, Chao Li, Fangzhao Li, Bao Jin, Shiyao National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China College of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9781509037261

Single image super-resolution reconstruction is a challenging ill-posed inverse problem currently. In this paper, we propose a method based on image classification and sparse representation for single image super-resolution reconstruction. Various images belong to different image category, and each category contains different contents and structures respectively, especially the high-frequency feature. Therefore, we extract the features of the input low-resolution image, and classify it into the corresponding category. Then the high-resolution image is reconstructed by sparse representation with the dictionary trained from the corresponding database, which consists of high-resolution and low-resolution image patch pairs. The experimental results demonstrate that our method achieves better performance in visual effect and qualitative analysis, by comparison with some well-known methods. © 2016 IEEE.

关键词： Image classification

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