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International Joint Conference on Neural Networks (IJCNN)

作者： Qin Jiang Qinglin Wang Lihua Chi Jie Liu Science and Technology on Parallel and Distributed Processing Laboratory Laboratory of Digitizing Software for Frontier Equipment Hunan GuoKe Computility Technology Co. Ltd

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Space-time video super-resolution (STVSR) is a comprehensive task comprising two subtasks: video super resolution in space dimension and video frame interpolation in time dimension. Conventional decoupled two-stage approaches tend to overlook the intrinsic correlation between the two tasks. Overcoming this challenge requires the development of a unified model capable of simultaneously implementing space-time super-resolution across arbitrary scales. Most existing models are confined to training on fixed space upsampling scales or specific frame-rate videos, resulting in limited generalization capabilities for flexible space-time super-resolution scenarios. In response to this limitation, our approach draws inspiration from continuous implicit neural representation. We propose an enhanced Implicit Neural Alignment Network (INAN) based on the VideoINR framework, encompassing feature refinement, precise motion flow estimation, and multi-scale feature fusion to optimize the final implicit neural decoding. Our extensive experimental evaluations on multiple benchmarks underscore the efficacy of the INAN model, indicate its superior performance compared to prior STVSR methods.

关键词： Training Interpolation Correlation Superresolution Neural networks Estimation Benchmark testing

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Research on Online Failure Prediction Model and Status Pretreatment Method for Exascale System

Research on Online Failure Prediction Model and Status Pretr...

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

作者： Hao Zhou Yanhuang Jiang National Laboratory of Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha China

The reliability issue of Exascale system is extremely serious. Traditional passive fault-tolerant methods, such as rollback-recovery, can not fully guarantee system reliability any more because of their large executing overhead and long recovering duration. Active fault tolerance is expected to become another important fault-tolerant approach for Exascale system. Focusing on system failure prediction, which is one key step of active fault tolerance, we construct online failure prediction model and research on the effective method of system status pretreatment. In order to improve the accuracy and real-time feature of current methods, the proposed Improved Adaptive Semantic Filter (IASF) method processes the latest system logs regularly, filtering useless information out of them according to their semantics. Adopting the main idea of Vector Space Model (VSM), IASF method creates Event Vector corresponding to each log record. By calculating the cosine of vectorial angle, it evaluates the semantics correlation between different log records, and then executes temporal and spatial redundant filter considering the burst feature of log records. IASF method is insensitive to the type of system log and does not introduce any expert system or domain knowledge. The experiment result shows that system can eliminate about 99.6% of useless log records after executing IASF method.

关键词： Fault tolerance Fault tolerant systems Vectors Correlation Information filters Predictive models

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A study of strategies to restrain the C&C activities of structured P2P botnets

A study of strategies to restrain the C&C activities of stru...

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International Conference on Computer sciences and Convergence Information technology (ICCIT)

作者： Tianzuo Wang Bo Liu Huaimin Wang Hao Ren Xiaolong Ma School of Computer Science National Laboratory for Parallel and Distributed Processing National University of Defense and Technology Changsha China

Botnets are threatening the Internet heavily, and more and more botnets are utilizing the P2P technology to build their C&C (Command and Control) mechanisms. Some research have been made to compare the resilience of structured P2P botnets and unstructured ones, against elimination of nodes, but the problem that which eliminating strategy is the best is rarely studied. In this paper, we proposed a new metric called the half point, to measure the effectiveness of different strategies. We also selected seven different eliminating strategies and compared them. Through extensive simulations, we find that RBC is the best eliminating strategy. Further analysis shows that for the strategy RBC, the average degree of nodes in the botnet have the most significant influence. The bigger the average degree is, the bigger the half point of RBC is, which implies that node eliminating may not be a reasonable choice for mitigating botnets with big average degree. Results of this paper can provide guidance for restraining structured P2P botnets.

关键词： C&C mechanism betweenness centrality coreness eliminating strategy half point restrain structured P2P botnets

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Providing Responsiveness Requirement Based Consistency in DVE

Providing Responsiveness Requirement Based Consistency in DV...

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International Conference on Parallel and distributed Systems (ICPADS)

作者： Wei Zhang Hangjun Zhou Yuxing Peng Sikun Li National Laboratory of Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha China

Consistency and responsiveness are two important factors in providing the sense of reality in distributed Virtual Environment (DVE). However, it is not easy to optimize both aspects because of the trade-off between these two factors. As a result, most existing consistency maintenance methods ignored the responsiveness requirements, or just assumed a simple responsiveness requirement model which cannot meet the real need of DVE systems. In this paper, we first present a new responsiveness requirement model. The model can describe requirement satisfaction situation of each node. Base on this model, we propose a responsiveness requirement based consistency method. The method can adjust the utilization of time resource according to the requirements of different nodes and improve the overall responsiveness performance by at least 20%. Therefore, it provides a good support to increase the applicability of DVE systems.

关键词： Delay effects Virtual environment distributed processing Computer science Games Distance learning Electronic commerce Safety Research and development Real time systems

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The prediction model based on RBF network in achieving elastic cloud

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Advances in Information sciences and Service sciences 2011年第11期3卷 67-78页

作者： Shi, Peichang Wang, Huaimin Ding, Bo Liu, Ran Wang, Tianzuo National Laboratory for Parallel and Distributed Processing School of Computer and Science National University of Defense Technology China Department of Electronics and Information Engineering Huazhong University of Science Technology China

Cloud needs to have rapid and elastic resources supply capability, because of the fluctuant resources demand of end-users. Multi-scale resources elastic binding is an important method to provide cloud services with rapid and elastic service capability. The most challenging problem in multi-scale resources elastic binding is how to predict the dynamic resource demand of end-users, and then decide when and to what extent multi-scale resources need elastic binding based on the prediction. In this paper, we present the prediction model based on RBF (Radial Basis Function) Network, which is used to predict end-users resource demand in advance. Compared with current prediction methods, it has faster prediction speed and higher prediction accuracy. Then we use traces data (the bandwidth demand of Web type of cloud services) collected from a real-world cloud provider: ChinaCache, as the training and testing data set to validate the method. Finally, we evaluate the predicted results using general prediction accuracy metrics. The results prove that the prediction model based on RBF network is able to resolve the decision problem in multi-scale resources elastic binding.

关键词： Radial basis function networks

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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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Optimization techniques of on-chip memory system based on UltraSPARC architecture

Optimization techniques of on-chip memory system based on Ul...

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Asia Pacific Conference on Postgraduate Research in Microelectronics & Electronics (PrimeAsia)

作者： Anwen Huang Jun Gao Chaochao Feng Minxuan Zhang Key Laboratory of Science and Technology of National Defense of Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha China

It is of great significance to optimize the design of on-chip memory system for improving the performance of multi-core processor. This paper describes the organization of on-chip memory hierarchy in UltraSPARC T2, analyzes the procedure of dealing with the memory access request from multi-core processor in detail. To get the basic parameters of timing characteristic and area consumption, the primary element of on-chip memory system is simulated by ModelSim and synthesized by Synopsys Design Complier with 90 nm standard cell library. Aimed at the potential limiting factor of improving the performance of memory hierarchy, corresponding optimization techniques of critical elements in memory system are explored finally.

关键词： System-on-a-chip Elliptic curve cryptography Hardware Costs Algorithm design and analysis Random access memory Clocks Registers Elliptic curves Protection

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Image Annotation by Object Hypotheses-oriented Deep Neural Networks

Image Annotation by Object Hypotheses-oriented Deep Neural N...

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2017 2nd International Conference on Software, Multimedia and Communication Engineering（SMCE 2017)

作者： Fang MA Shao-he LV Ke-xin ZHENG Chi JIN Fei CHEN Ke YANG and Yong DOU National Laboratory for Parallel and Distributed Processing National University of Defense Technology University of South China School of Computer Science and Technology

Image annotation generates a set of semantic labels that describe the contents of an input *** deep learning techniques have achieved significant success in many areas of image *** this paper,we present a multi-label image annotation method that combines unsupervised object hypotheses generation and deep neural *** an image,object hypotheses are generated in an unsupervised *** we extract the image features for each hypothesis with a deep neural network *** combining the features of all hypotheses,we get the features of the entire ***,we calculate for each label the probability of that the label is correlated with the given *** can be trained in an end-to-end way using the standard backward propagation *** results on multiple benchmark datasets show that our method is better than the state-of-the-art ones.

关键词： Deep learning Multi-label annotation Object hypotheses

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DRAM failure prediction in AIOps: Empirical evaluation, challenges and opportunities

arXiv

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arXiv 2021年

作者： Wu, Zhiyue Xu, Hongzuo Pang, Guansong Yu, Fengyuan Wang, Yijie Jian, Songlei Wang, Yongjun Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology China University of Adelaide Australia

DRAM failure prediction is a vital task in AIOps, which is crucial to maintain the reliability and sustainable service of large-scale data centers. However, limited work has been done on DRAM failure prediction mainly due to the lack of public available datasets. This paper presents a comprehensive empirical evaluation of diverse machine learning techniques for DRAM failure prediction using a large-scale multi-source dataset, including more than three millions of records of kernel, address, and mcelog data, provided by Alibaba Cloud through PAKDD 2021 competition. Particularly, we first formulate the problem as a multi-class classification task and exhaustively evaluate seven popular/state-of-the-art classifiers on both the individual and multiple data sources. We then formulate the problem as an unsupervised anomaly detection task and evaluate three state-of-the-art anomaly detectors. Further, based on the empirical results and our experience of attending this competition, we discuss major challenges and present future research opportunities in this task. © 2021, CC BY.

关键词： Web services

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Some critical problems of botnets

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Jisuanji Xuebao/Chinese Journal of Computers 2012年第6期35卷 1192-1208页

作者： Wang, Tian-Zuo Wang, Huai-Min Liu, Bo Shi, Pei-Chang Institute of Network and Information Security School of Computer Science National University of Defense Technology Changsha 410073 China National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha 410073 China

As a complex, flexible and effective platform for network attacking, the botnet spreads widely in the Internet. Botnets can provide the botmasters with the ability to launch large-scale malicious activities such as spamming and DDoS (distributed Denial of Service) attacks. Botnets are continuously bringing more and more severe threats, so that the study on botnets has already become one of the focuses in the field of network security. However, in recent years, some new developments of botnets are challenging the existing understanding on botnets. In this paper, according to the new conditions of botnets and the researches in existence, a definition of botnet is proposed based on the works of other researchers, taxonomies of botnets are introduced respectively from the views of network structure, dependency and delivery pattern of C&C (Command and Control) information. Then the techniques on detecting, measuring and restraining botnets are analyzed systematically. In the end, we give the evolution trends of botnets and the future research trends in this area.

关键词： Botnet

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