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2015 IEEE 16th International Conference on Communication Technology(ICCT 2015)

作者： Xiang Zhang Naiyang Guan Zhigang Luo College of Computer National University of Defense Technology National Laboratory for Parallel and Distributed Processing National University of Defense Technology

Sparse coding has shown its great potential in learning image feature representation. Recent developed methods such as group sparse coding prefer discovering the group relationships among examples and have achieved the state-of-the-art results in image classification. However, they suffer from poor robustness shortcomings in practice. This paper proposes a robust weighted supervised sparse coding method(RWSSC) to address this ***, RWSSC distinguishes different classes' contributions to the sparse coding by a novel weighting strategy meanwhile removes the out liers by imposing1 l-regularization over the noisy entries. Benefitting from these strategies, RWSSC can effectively boost performance of sparse coding in image ***, we developed the block coordinate descent algorithm to optimize it, and proved its *** results of image classification on two popular datasets show that RWSSC outperforms the representative sparse coding methods in quantities.

关键词： Sparse coding Supervised learning Image classification

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Efficient distributed Data Clustering on Spark

Efficient Distributed Data Clustering on Spark

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IEEE International Conference on Cluster Computing

作者： Jia Li Dongsheng Li Yiming Zhang National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha China

ISBN: (纸本)9781467365994

Data clustering is usually time-consuming since it by default needs to iteratively aggregate and process large volume of data. Approximate aggregation based on sample provides fast and quality ensured results. In this paper, we propose to leverage approximation techniques to data clustering to obtain the trade-off between clustering efficiency and result quality, along with online accuracy estimation. The proposed method is based on the bootstrap trials. We implemented this method as an Intelligent Bootstrap Library (IBL) on Spark to support efficient data clustering. Intensive evaluations show that IBL can provide a 2x speed-up over the state of art solution with the same error bound.

关键词： Sparks Accuracy Data mining Estimation error distributed databases Approximation methods

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MABP: an optimal resource allocation approach in data center networks

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Science China(Information Sciences) 2014年第10期57卷 230-245页

作者： LI XiaoLing WANG HuaiMin DING Bo LI XiaoYong National Key Laboratory for Parallel and Distributed Processing School of ComputerNational University of Defense Technology

In data center networks, resource allocation based on workload is an effective way to allocate the infrastructure resources to diverse cloud applications and satisfy the quality of service for the users, which refers to mapping a large number of workloads provided by cloud users/tenants to substrate network provided by cloud providers. Although the existing heuristic approaches are able to find a feasible solution, the quality of the solution is not guaranteed. Concerning this issue, based on the minimum mapping cost, this paper solves the resource allocation problem by modeling it as a distributed constraint optimization problem. Then an efficient approach is proposed to solve the resource allocation problem, aiming to find a feasible solution and ensuring the optimality of the solution. Finally, theoretical analysis and extensive experiments have demonstrated the effectiveness and efficiency of our proposed approach.

关键词： data center network resource allocation workload substrate network optimality distributed constraint optimization

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RaceChecker: Efficient Identification of Harmful Data Races

RaceChecker: Efficient Identification of Harmful Data Races

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Euromicro Conference on parallel, distributed and Network-Based processing

作者： Kai Lu Zhendong Wu Xiaoping Wang Chen Chen Xu Zhou Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha PR China

ISBN: (纸本)9781479984923

Data races hidden in concurrent programs have caused severe failures. To improve the reliability, many race detectors are proposed. However, most of the reported races are not harmful, which consumes manual effort to identify the harmful races. This paper proposes RaceChecker that can detect the potential races and identify the harmful races effectively and efficiently. Unlike previous detectors, RaceChecker combines happens-before relation and ad-hoc synchronization to prune the infeasible races so that fewer potential races are required to be verified. Before verification, RaceChecker groups the remaining potential races, guaranteeing the potential races in one group do not interfere with each other. Therefore, multiple potential races in one group can be verified together in one execution. To our knowledge, this is the first effective technique that groups the potential races to improve the efficiency. Unlike previous detectors that verify one potential race in one execution, RaceChecker dynamically controls thread scheduler to create real race conditions to verify multiple potential races in one execution, identifying the harmful races that cause program failures. We have implemented RaceChecker as a prototype tool and have experimented on a number of real-world concurrent programs. Results show that 66% of the potential races are infeasible and nearly 48% of the executions are reduced by the grouping strategy. The known harmful races are also identified effectively. By pruning and grouping, RaceChecker identifies the harmful races more efficiently. Comparing with RaceMob and RaceFuzzer, the time is reduced significantly, with an average of 45% and 81% respectively.

关键词： Detectors Synchronization Concurrent computing Programming Relays Instruction sets Monitoring

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Feverfew: a scalable coverage-based hybrid overlay for Internet-scale pub/sub networks

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Science China(Information Sciences) 2014年第5期57卷 51-64页

作者： MA XingKong WANG YiJie SUN WeiDong National Key Laboratory for Parallel and Distributed Processing School of ComputerNational University of Defense Technology

The publish/subscribe(pub/sub)paradigm is a popular communication model for data dissemination in large-scale distributed ***,scalability comes with a contradiction between the delivery latency and the memory *** one hand,constructing a separate overly per topic guarantees real-time dissemination,while the number of node degrees rapidly increases with the number of *** the other hand,maintaining a bounded number of connections per node guarantees small memory cost,while each message has to traverse a large number of uninterested nodes before reaching the *** this paper,we propose Feverfew,a coverage-based hybrid overlay that disseminates messages to all subscribers without uninterested nodes involved in,and increases the average number of node connections slowly with an increase in the number of subscribers and *** major novelty of Feverfew lies in its heuristic coverage mechanism implemented by combining a gossip-based sampling protocol with a probabilistic searching *** on the practical workload,our experimental results show that Feverfew significantly outperforms existing coverage-based overlay and DHT-based overlay in various dynamic network environments.

关键词： publish/subscribe coverage-based data dissemination topic-based gossip

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AutoMal: Automatic clustering and signature generation for malwares based on the network flow

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Security and Communication Networks 2015年第10期8卷 1845-1854页

作者： Hao, Sun Wang, Wen Lu, Huabiao Ren, Peige School of Computer National University of Defense Technology Changsha China National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

The volume of malwares is growing at an exponential speed nowadays. This huge growth makes it extremely hard to analyse malware manually. Most existing signatures extracting methods are based on string signatures, and string matching is not accurate and time consuming. Therefore, this paper presents AutoMal, a system for automatically extracting signatures from large-scale malwares. Firstly, the system proposes to represent the network flows by using feature hashing, which can dramatically reduce the high-dimensional feature spaces that are general in malware analysis. Then, we design a clustering and median filtering method to classify the malware vectors into different types. Finally, it introduces the signature generation algorithm based on Bayesian method. The system can extract both the byte signature and the hash signature of malwares from its network flow with low false positive and zero false negative. Our evaluation shows that AutoMal can generate strongly noise-resisted signatures that exactly depict the characteristics of malware. © 2014 John Wiley & Sons, Ltd.

关键词： Malware

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MatrixMap: Programming Abstraction and Implementation of Matrix Computation for Big Data Applications

MatrixMap: Programming Abstraction and Implementation of Mat...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Yaguang Huangfu Jiannong Cao Hongliang Lu Guanqing Liang Department of Computing The Hong Kong Polytechnic University Parallel and Distributed Processing Laboratory National University of Defense Technology

The computation core of many big data applications can be expressed as general matrix computations, including linear algebra operations and irregular matrix operations. However, existing parallel programming systems such as Spark do not have programming abstraction and efficient implementation for general matrix computations. In this paper, we present MatrixMap, a unified and efficient data-parallel system for general matrix computations. MatrixMap provides powerful yet simple abstraction, consisting of a distributed data structure called bulk key matrix and a computation interface defined by matrix patterns. Users can easily load data into bulk key matrices and program algorithms into parallel matrix patterns. MatrixMap outperforms current state-of-the-art systems by employing three key techniques: matrix patterns with lambda functions for irregular and linear algebra matrix operations, asynchronous computation pipeline with optimized data shuffling strategies for specific matrix patterns and in-memory data structure reusing data in iterations. Moreover, it can automatically handle the parallelization and distribute execution of programs on a large cluster. The experiment results show that MatrixMap is 12 times faster than Spark.

关键词： Data structures Programming Linear algebra Machine learning algorithms Sparks Sparse matrices Computational modeling

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Virtual Frame Aggregation: Clustered Channel Access in Wireless Networks

Virtual Frame Aggregation: Clustered Channel Access in Wirel...

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IEEE International Conference on Communications

作者： Xuan Dong Shaohe Lv Chunsheng Zhu Rukhsana Ruby Xiaodong Wang Xingming Zhou Victor C. M. Leung National Laboratory of Parallel and Distributed Processing National University of Defense Technology Department of Electrical and Computer Engineering The University of British Columbia

ISBN: (纸本)9781467364300

Coordination among users is inevitable in wireless communication for efficient medium access. Even though the data rate of individual user increases significantly, the performance of wireless network does not grow up accordingly due to the high MAC coordination overhead. In this paper, we present VFA, namely virtual frame aggregation, to achieve high coordination efficiency by amortizing the overhead over multiple transmissions. VFA provides a novel way to construct a winner cluster and allow the winners to transmit without interruption. Specifically, in a multicarrier network, every contending node chooses a subcarrier and the nodes are ordered by the index of the chosen subcarrier. When there are some subcarriers chosen by two or more nodes, an additional slot is exploited to reorder the collided nodes. Finally, all ordered nodes form a cluster and the transmissions are issued sequentially and uninterruptedly. Simulation results show that usually two slots are enough to construct a sufficiently large winner cluster. Moreover, VFA achieves a notable throughput gain over IEEE 802.11 as high as 120% with better fairness under various scenarios.

关键词： Wireless communication Antennas Wires

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Design, Implementation and Evaluation of an Application-Layer Virtualized Network

Design, Implementation and Evaluation of an Application-Laye...

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2015 IEEE Symposium on Service-Oriented System Engineering

作者： Yiming Zhang Dongsheng Li Yijie Wang Zhigang Sun Feng Zhao Jinshu Su National University of Defense Technology Changsha Hunan CN School of Computer National Laboratory for Parallel and Distributed Processing (PDL) Changsha China

The performance of virtualized networks is critical to cloud applications. The "distributed line graphs" (DLG) are a universal technique for designing network topologies based on arbitrary regular graphs. In this paper we implement a prototype (C library) for a DLG-enabled network (called DLG-Kautz), as an application-layer virtualized network service. The effectiveness of our design and implementation is demonstrated through prototype evaluations.

关键词： Routing Message systems Ports (Computers) Servers Payloads Prototypes Libraries

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Experimental verification of the parasitic bipolar amplification effect in PMOS single event transients

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Chinese Physics B 2014年第7期23卷 775-779页

作者：何益百陈书明 College of Computer National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology

The contribution of parasitic bipolar amplification to SETs is experimentally verified using two P-hit target chains in the normal layout and in the special layout. For PMOSs in the normal layout, the single-event charge collection is composed of diffusion, drift, and the parasitic bipolar effect, while for PMOSs in the special layout, the parasitic bipolar junction transistor cannot turn on. Heavy ion experimental results show that PMOSs without parasitic bipolar amplification have a 21.4% decrease in the average SET pulse width and roughly a 40.2% reduction in the SET cross-section.

关键词： single event effect single event transient parasitic bipolar amplification heavy ion experiments

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