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31st ACM International Conference on Supercomputing, ICS 2017

作者： Shi, Xuanhua Li, Ming Liu, Wei Jin, Hai Yu, Chen Chen, Yong Services Computing Technology and System Lab Big Data Technology and System Lab Huazhong University of Science and Technology Wuhan430074 China Department of Computer Science Texas Tech University LubbockTX United States

ISBN: (纸本)9781450350204

Many high performance computing (HPC) applications are highly data intensive. Current HPC storage systems still use hard disk drives (HDDs) as their dominant storage devices, which suffer from disk head thrashing when accessing random data. New storage devices such as solid state drives (SSDs), which can handle random data access much more efficiently, have been widely deployed as the buffer to HDDs in many production HPC systems. Burst buffer has also been proposed to manage the SSD buffering of bursty write requests. Although burst buffer can improve I/O performance in many cases, we find that it has some limitations such as requiring large SSD capacity and harmonious overlapping between computation phase and data flushing stage. In this paper, we propose a scheme, called SSDUP (a traffic-aware SSD burst buffer), to improve the burst buffer by addressing the above limitations. In order to reduce the SSD capacity demand, we 5develop a novel traffic-detection method to detect the randomness in the write traffic. Based on this method, only the random writes are buffered to SSD and other writes are deemed sequential and propagated to HDDs directly. In order to overcome the difficulty of perfectly overlapping the computation phase and the flushing stage, we propose a pipeline mechanism for the SSD buffer, in which the data buffering and data flushing are performed in pipeline. Finally, in order to further improve the performance of buffering random writes in SSD, we covert the random writes to sequential writes in SSD by storing the data with a log structure. Further, we propose to use the AVL tree structure to store the sequence information of the data. We have implemented a prototype of SSDUP based on the OrangeFS and performed extensive experimental evaluation. The experimental results show that the proposed SSDUP scheme can improve the write performance by more than 50% on average. © 2017 Association for Computing Machinery.

关键词： Trees (mathematics)

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Zero-determinant Strategies for Three-player in Finitely Repeated Games

Zero-determinant Strategies for Three-player in Finitely Rep...

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第37届中国控制会议

作者： Jianzhang Chen Zhihai Rong College of Computer and Information Sciences Fujian Agriculture and Forestry University CompleX Lab Web Sciences CenterUniversity of Electronic Science and Technology of China Big Data Research Center University of Electronic Science and Technology of China School of Computer Science and Engineering University of Electronic Science and Technology of China

Zero-determinant strategies are a new class of probabilistic and conditional strategies, where a player can use a linear relationship between his own payoff and the opponents payoff to determine his opponents expected payoff or extort his opponents unilaterally. This paper will analysis a model of zero-determinant strategies for three players in the finitely repeated public goods game（with a discount factor δ satisfying 0 ＜ δ ＜ 1）. Via analyzing these strategies for three players in the game, including equalizer strategies, extortion strategies and generous strategies, it finds that a player also has an ability to pin the expected total payoff of all other players in a unilateral way as the two-player model by equalizer strategies and can set a ratio between his payoff and the total payoff of all other players by the extortion strategies, and the expected payoffs of three players can obtain the same payoff when they cooperate in the first round by using generous strategies. This provides potential clues to design efficient cooperation protocol in multi-agent systems.

关键词： Zero-determinant Strategies Finitely Repeated Games Direct reciprocity Discount factor

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Sysevr: A framework for using deep learning to detect software vulnerabilities

arXiv

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arXiv 2018年

作者： Li, Zhen Zou, Deqing Xu, Shouhuai Jin, Hai Zhu, Yawei Chen, Zhaoxuan Services Computing Technology and System Lab Cluster and Grid Computing Lab Big Data Security Engineering Research Center School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Department of Computer Science University of Texas at San Antonio San AntonioTX78249 United States

The detection of software vulnerabilities (or vulnerabilities for short) is an important problem that has yet to be tackled, as manifested by many vulnerabilities reported on a daily basis. This calls for machine learning methods to automate vulnerability detection. Deep learning is attractive for this purpose because it does not require human experts to manually define features. Despite the tremendous success of deep learning in other domains, its applicability to vulnerability detection is not systematically understood. In order to fill this void, we propose the first systematic framework for using deep learning to detect vulnerabilities. The framework, dubbed Syntax-based, Semantics-based, and Vector Representations (SySeVR), focuses on obtaining program representations that can accommodate syntax and semantic information pertinent to vulnerabilities. Our experiments with 4 software products demonstrate the usefulness of the framework: we detect 15 vulnerabilities that are not reported in the National Vulnerability database. Among these 15 vulnerabilities, 7 are unknown and have been reported to the vendors, and the other 8 have been "silently" patched by the vendors when releasing newer versions of the products. Copyright © 2018, The Authors. All rights reserved.

关键词： Syntactics

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Partial-order Algorithm of Model Checking in µ-Predicate Ambient Logic

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Journal of Computers (Taiwan) 2018年第5期29卷 142-159页

作者： Jiang, Hua Lin, Rong-De Zou, Fu-Min Li, Ling-Xiang Key Lab of Granular Computing Minnan Normal University ZhangZhou China School of Mathematical Science Huaqiao university QuanZhou China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fuzhou Fujian350008 China School of Electronics and Information Engineering Hunan University of Science and Engineering Yongzhou425199 China

This paper introduces a kind of partial-order algorithm of model-checking in finite-control mobile ambients against μ-predicate ambient logic(Ambient logic based on first-order μ-calculus). Based on Tarski's fixpoint theorem, nested predicate equations and Block Dependency Graph, a group of partial ordering relation between inter-mediate results in the process of model checking is given, and thus a kind of local model-checking algorithm is proposed. To our knowledge, this is the first algorithm which exponent of time complexity is d/2+2, the exponent of space complexity is d/2 (d is the alternate nesting depth of fixpoint operator in the formula) and this is the third model-checking algorithm for predicate ambient logic with recursion. This paper's contributions are: (1) getting a group of partial ordering relation between intermediate results in the computing process of model checking for µ-calculus first-order predicate ambient logic based on Tarski's fixpoint theorem;(2) using the partial ordering relation to design an algorithm for model checking in mobile ambients;(3) analyzing the complexity of the algorithm. © 2018 Computer Society of the Republic of China. All rights reserved.

关键词： Model checking

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Software Defined Networking Based On-Demand Routing Protocol in Vehicle Ad-Hoc Networks

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ZTE Communications 2017年第2期15卷 11-18页

作者： DONG Baihong WU Weigang YANG Zhiwei LI Junjie Guangdong Province Key Lab. of Big Data Analysis and Processing School of Data and Computer Science Sun Yat-Sen University Guangzhou 510006 China

This paper comes up with a SDN Based Vehicle Ad-Hoc On-Demand Routing Protocol(SVAO),which separates the data forwarding layer and network control layer,as in software defined networking(SDN),to enhance data transmission efficiency within vehicle ad-hoc networks(VANETs).The roadside service unit plays the role of local controller and is in charge of selecting vehicles to forward packets within a road *** the vehicles state in the ***,a two-level design is *** global level is distributed and adopts a ranked query scheme to collect vehicle information and determine the road segments along which a message should be *** the other hand,the local level is in charge of selecting forwarding vehicles in each road segment determined by the global *** implement two routing algorithms of SVAO,and compare their performance in our *** compare SVAO with popular ad-hoc network routing protocols,including Optimized Link State Routing(OLSR),Dynamic Source Routing(DSR),Destination Sequence Distance Vector(DSDV),and distance-based routing protocol(DB)via *** consider the impact of vehicle density,speed on data transmission rate and average packet *** simulation results show that SVAO performs better than the others in large-scale networks or with high vehicle speeds.

关键词： VANETs SDN routing protocol ad.hoc network Internet of Vehicle

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Automatic Extraction of Medication Mentions from Tweets-Overview of the BioCreative VII Shared Task 3 Competition

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database : the journal of biological databases and curation 2023年第2023期2023卷 baac108页

作者： Davy Weissenbacher Karen O'Connor Siddharth Rawal Yu Zhang Richard Tzong-Han Tsai Timothy Miller Dongfang Xu Carol Anderson Bo Liu Qing Han Jinfeng Zhang Igor Kulev Berkay Köprü Raul Rodriguez-Esteban Elif Ozkirimli Ammer Ayach Roland Roller Stephen Piccolo Peijin Han V G Vinod Vydiswaran Ramya Tekumalla Juan M Banda Parsa Bagherzadeh Sabine Bergler João F Silva Tiago Almeida Paloma Martinez Renzo Rivera-Zavala Chen-Kai Wang Hong-Jie Dai Luis Alberto Robles Hernandez Graciela Gonzalez-Hernandez Department of Computational Biomedicine Cedars-Sinai Medical Center Los Angeles CA USA. DBEI The Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Computer Science and Information Engineering National Central University No. 300 Zhongda Rd Zhongli District Taoyuan 320 Taiwan. IoX Center National Taiwan University Da'an District Section 4 Roosevelt Rd No. 1 Barry Lam Hall Taipei 106 Taiwan. Research Center for Humanities and Social Sciences Academia Sinica No. 128 Section 2 Academia Rd Nangang District Taipei 115 Taiwan. Computational Health Informatics Program Boston Children's Hospital Boston MA USA. Department of Pediatrics Harvard Medical School Boston MA USA. NVIDIA Santa Clara CA USA. Department of Statistics Florida State University Tallahassee FL USA. Data and Analytics Chapter F. Hoffmann-La Roche Ltd Switzerland. Pharmaceutical Research and Early Development Roche Innovation Center Basel Switzerland. Speech and Language Technology Lab DFKI Berlin Germany. Department of Biology Brigham Young University Provo UT USA. Department of Computational Medicine and Bioinformatics Medical School University of Michigan Ann Arbor MI USA. Department of Learning Health Sciences Medical School University of Michigan Ann Arbor MI USA. School of Information University of Michigan Ann Arbor MI USA. Department of Computer Science Georgia State University Atlanta GA USA. CLaC Labs Concordia University Montreal Canada. DETI Institute of Electronics and Informatics Engineering of Aveiro University of Aveiro Portugal. Department of Computation University of A Coruña Spain. Computer Science and Engineering Department Universidad Carlos III de Madrid Madrid Spain. Big Data Laboratory Chunghwa Telecom Laboratories Taoyuan Taiwan. Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan. Department of Electrical Engineering College of Electrical Engineering and Computer Sci

This study presents the outcomes of the shared task competition BioCreative VII (Task 3) focusing on the extraction of medication names from a Twitter user's publicly available tweets (the user's 'timeline'). In general, detecting health-related tweets is notoriously challenging for natural language processing tools. The main challenge, aside from the informality of the language used, is that people tweet about any and all topics, and most of their tweets are not related to health. Thus, finding those tweets in a user's timeline that mention specific health-related concepts such as medications requires addressing extreme imbalance. Task 3 called for detecting tweets in a user's timeline that mentions a medication name and, for each detected mention, extracting its span. The organizers made available a corpus consisting of 182 049 tweets publicly posted by 212 Twitter users with all medication mentions manually annotated. The corpus exhibits the natural distribution of positive tweets, with only 442 tweets (0.2%) mentioning a medication. This task was an opportunity for participants to evaluate methods that are robust to class imbalance beyond the simple lexical match. A total of 65 teams registered, and 16 teams submitted a system run. This study summarizes the corpus created by the organizers and the approaches taken by the participating teams for this challenge. The corpus is freely available at https://***/tasks/biocreative-vii/track-3/. The methods and the results of the competing systems are analyzed with a focus on the approaches taken for learning from class-imbalanced data.

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A particle filter based multi-objective optimization algorithm: PFOPS

arXiv

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arXiv 2018年

作者： Liu, Bin Jin, Yaochu School of Computer Science Nanjing University of Posts and Telecommunications Jiangsu Key Lab of Big Data Security and Intelligent Processing Nanjing Jiangsu210023 China Department of Computer Science University of Surrey Guildford SurreyGU2 7XH United Kingdom

This paper is concerned with a recently developed paradigm for population-based optimization, termed particle filter optimization (PFO). This paradigm is attractive in terms of coherence in theory and easiness in mathematical analysis and interpretation. Current PFO algorithms only work for single-objective optimization cases, while many real-life problems involve multiple objectives to be optimized simultaneously. To this end, we make an effort to extend the scope of application of the PFO paradigm to multi-objective optimization (MOO) cases. An idea called path sampling is adopted within the PFO scheme to balance the different objectives to be optimized. The resulting algorithm is thus termed PFO with Path Sampling (PFOPS). The validity of the presented algorithm is assessed based on three benchmark MOO experiments, in which the shapes of the Pareto fronts are convex, concave and discontinuous, respectively. Copyright © 2018, The Authors. All rights reserved.

关键词： Monte Carlo methods

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DroidAuditor: A framework for auditing covert communication on Android

DroidAuditor: A framework for auditing covert communication ...

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作者： Qiang, Weizhong Xin, Shifan Jin, Hai Sun, Guozhong Services Computing Technology and System Lab Cluster and Grid Computing Lab Big Data Technology and System Lab Huazhong University of Science and Technology Wuhan430074 China Co. Ltd. Beijing100193 China

Exploitation of covert channels in smartphone operating systems may lead to furtive data transmission between applications with different permissions, which might threaten users' privacy. Restricting the access to shared system resources can effectively prevent the exploitation of known covert channels. However, it inevitably limits the normal usage of those resources. In this paper, we propose a general method that detects covert channel attack at runtime without impacting the accessibility of shared resources in the system. The main idea of the method is to track and audit the use of system resources known as potential covert channel variables and impose interferences on those channels to reduce their capacity once violations are detected. We implement a prototype framework, which is able to audit and interfere covert communication both in the application layer and in the native layer of Android. The experimental results demonstrate that our method can effectively reduce the data rate of user-defined covert channels while the overhead is negligible. Copyright © 2017 John Wiley & Sons, Ltd.

关键词： Android (operating system)

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Part-based visual tracking via structural support correlation filter

arXiv

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arXiv 2018年

作者： Ji, Zhangjian Feng, Kai Qian, Yuhua School of Computer and Information Technology Shanxi University Taiyuan China Key Lab. of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi University Taiyuan China Institute of Big Data Science and Industry Shanxi University Taiyuan China

Recently, part-based and support vector machines (SVM) based trackers have shown favorable performance. Nonetheless, the time-consuming online training and updating process limit their real-time applications. In order to better deal with the partial occlusion issue and improve their efficiency, we propose a novel part-based structural support correlation filter tracking method, which absorbs the strong discriminative ability from SVM and the excellent property of part-based tracking methods which is less sensitive to partial occlusion. Then, our proposed model can learn the support correlation filter of each part jointly by a star structure model, which preserves the spatial layout structure among parts and tolerates outliers of parts. In addition, to mitigate the issue of drift away from object further, we introduce inter-frame consistencies of local parts into our model. Finally, in our model, we accurately estimate the scale changes of object by the relative distance change among reliable parts. The extensive empirical evaluations on three benchmark datasets: OTB2015, TempleColor128 and VOT2015 demonstrate that the proposed method performs superiorly against several state-of-the-art trackers in terms of tracking accuracy, speed and robustness. Copyright © 2018, The Authors. All rights reserved.

关键词： Support vector machines

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Link prediction via linear optimization

arXiv

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arXiv 2018年

作者： Pech, Ratha Hao, Dong Lee, Yan-Li Yuan, Ye Zhou, Tao CompleX Lab University of Electronic Science and Technology of China Chengdu611731 China Big Data Research Center University of Electronic Science and Technology of China Chengdu611731 China School of Automation State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China

Link prediction is an elemental challenge in network science, which has already found applications in guiding laboratorial experiments, digging out drug targets, recommending online friends, probing network evolution mechanisms, and so on. With a simple assumption that the likelihood of the existence of a link between two nodes can be unfolded by a linear summation of neighboring nodes' contributions, we obtain the analytical solution of the optimal likelihood matrix, which shows remarkably better performance in predicting missing links than the state-of-the-art algorithms for not only simple networks, but also weighted and directed networks. To our surprise, even some degenerated local similarity indices from the solution outperform well-known local indices, which largely refines our knowledge, for example, the number of 3-hop paths between two nodes more accurately predicts missing links than the number of 2-hop paths (i.e., the number of common neighbors), while in previous methods, longer paths are always considered to be less important than shorter paths. Copyright © 2018, The Authors. All rights reserved.

关键词： Forecasting

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