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3rd International Conference on Blockchain and Trustworthy Systems, Blocksys 2021

作者： Li, Linhui Shi, Peichang Fu, Xiang Zhang, Shengtian Zhong, Tao Chen, Ming National Key Laboratory of Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789811679926

In the Internet of Everything (IoE), due to its issues of complexity and heterogeneity, message delay cannot be guaranteed, and it is not enough to leverage a centralized model for data collaboration. By leveraging the features of blockchain and asynchronous consensus algorithms, a new trust collaboration model can be established in an untrusted environment. Besides, the scalability issue of blockchain poses a challenge to data asynchronous collaboration. In this paper, we propose Asycome, a JointCloud data asynchronous collaboration mechanism based on Directed Acyclic Graph (DAG). This mechanism introduces the new Gossip about gossip protocol, driven by message-transmitting events, to keep data synchronized in an asynchronous environment. Through two stages of voting and committing. Transactions on the same time series do not need to reach the final confirmed state before proceeding to the next transaction processing. Over time, all transactions are connected to the DAG, ensuring that the consensus is finally reached. We evaluated the performance of the mechanism with experiments on throughput and latency. And the feasibility of Asycome is analyzed from the liveness and security. The results show that higher throughput, lower latency, and Asynchronous Byzantine Fault Tolerance (ABFT) characteristics can meet the technical requirements of complex and asynchronous data collaboration of the IoE to some extent. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Blockchain

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Modeling complex relationship paths for knowledge graph completion

Modeling complex relationship paths for knowledge graph comp...

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作者： Zeng, Ping Tan, Qingping Meng, Xiankai Zhang, Haoyu Xu, Jianjun College of Computer National University of Defense Technology Changsha China National Key Laboratory for Parallel and Distributed Processing Changsha China

Determining the validity of knowledge triples and filling in the missing entities or relationships in the knowledge graph are the crucial tasks for large-scale knowledge graph completion. So far, the main solutions use machine learning methods to learn the low-dimensional distributed representations of entities and relationships to complete the knowledge graph. Among them, translationmodels obtain excellent performance. However, the proposed translation models do not adequately consider the indirect relationships among entities, affecting the precision of the representation. Based on the long short-term memory neural network and existing translation models, we propose a multiple-module hybrid neural network model called TransP. By modeling the entity paths and their relationship paths, TransP can effectively excavate the indirect relationships among the entities, and thus, improve the quality of knowledge graph completion tasks. Experimental results show that TransP outperforms state-of-the-art models in the entity prediction task, and achieves the comparable performance with previous models in the relationship prediction task. © 2018 The Institute of Electronics, Information and Communication Engineers.

关键词： Knowledge graph

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Support efficient and fault-tolerant multicast in bufferless network-on-chip

Support efficient and fault-tolerant multicast in bufferless...

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作者： Feng, Chaochao Lu, Zhonghai Jantsch, Axel Zhang, Minxuan Yang, Xianju National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology China Department of Electronic Systems Royal Institute of Technology Sweden

SUMMARY In this paper, we propose three Deflection-Routing-based Multicast (DRM) schemes for a bufferless NoC. The DRM scheme without packets replication (DRM-noPR) sends multicast packet through a non deterministic path. The DRM schemes with adaptive packets replication (DRM-PR-src and DRMYR-all) replicate multicast packets at the source or intermediate node according to the destination position and the state of output ports to reduce the average multicast latency. We also provide fault tolerant supporting in these schemes through a reinforcement learning based method to reconfigure the routing table to tolerate permanent faulty links in the network. Simulation results illustrate that the DRM-PR-all scheme achieves 4l6o, 43cc and 37% less latency on average than that of the DRM-noPR scheme and 27cc, 29cc and 2S6o less latency on average than that of the DRM-PR-src scheme under three synthetic traffic patterns respectively. In addition, all three fault tolerant DRM schemes achieve acceptable performance degradation at various link fault rates without any packet lost. Copyright © 2012 The Institute of Electronics, Information and Communication Engineers.

关键词： Network-on-chip

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Ladder: A Blockchain Model of Low-Overhead Storage 3rd

Ladder: A Blockchain Model of Low-Overhead Storage

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3rd International Conference on Blockchain and Trustworthy Systems, Blocksys 2021

作者： Chen, Peng Zhang, Xunhui Liu, Hui Xiang, Liangliang Shi, Peichang National Key Laboratory of Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789811679926

Emerging blockchain accounting mechanism allow mutually distributed parties to transport trusted information and ensure the correctness of data. Every blockchain node stores the complete block locally. Although this measure improves security, it causes huge storage overhead. We present Ladder, a multi-level low-overhead storage model for blockchain, which can greatly reduce the storage overhead of nodes while ensuring that the blockchain cannot be tampered easily and the block information is complete. Ladder distinguishes the retrieved frequency and importance of different blocks by value-density, dividing them into Hot-Blocks, Warm-Blocks and Cold-Blocks adopting different storage strategies respectively. Through experimental verification of time and space cost of different storage strategies, Ladder can greatly reduce the local storage overhead of nodes. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Blockchain

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Merge-Weighted Dynamic Time Warping for Speech Recognition

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Journal of computer Science & Technology 2014年第6期29卷 1072-1082页

作者：张湘莉兰骆志刚李明 State Key Laboratory of Pathogen and Biosecurity Beijing Institute of Microbiology and Epidemiology Science and Technology on Parallel and Distributed Processing Laboratory School of Computer Science National University of Defense Technology David R.Cheriton School of Computer Science University of WaterlooWaterlooOntario N2L 3G1Canada ACM IEEE

Obtaining training material for rarely used English words and common given names from countries where English is not spoken is difficult due to excessive time, storage and cost factors. By considering personal privacy, language- independent （LI） with lightweight speaker-dependent （SD） automatic speech recognition （ASR） is a convenient option to solve tile problem. The dynamic time warping （DTW） algorithm is the state-of-the-art algorithm for small-footprint SD ASR for real-time applications with limited storage and small vocabularies. These applications include voice dialing on mobile devices, menu-driven recognition, and voice control on vehicles and robotics. However, traditional DTW has several lhnitations, such as high computational complexity, constraint induced coarse approximation, and inaccuracy problems. In this paper, we introduce the merge-weighted dynamic time warping （MWDTW） algorithm. This method defines a template confidence index for measuring the similarity between merged training data and testing data, while following the core DTW process. MWDTW is simple, efficient, and easy to implement. With extensive experiments on three representative SD speech recognition datasets, we demonstrate that our method outperforms DTW, DTW on merged speech data, the hidden Markov model （HMM） significantly, and is also six times faster than DTW overall.

关键词： merge-weighted dynamic time warping natural language processing speech recognition and synthesis tem-plate confidence index

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DFTracker: detecting double-fetch bugs by multi-taint parallel tracking

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Frontiers of computer Science 2019年第2期13卷 247-263页

作者： Pengfei WANG Kai LU Gen LI Xu ZHOU Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha 410073 China College of Computer National University of Defense Technology Changsha 410073 China Collaborative Innovation Center of High Performance Computing National University of Defense Technology Changsha 410073 China

A race condition is a common trigger for concurrency bugs. As a special case, a race condition can also occur across the kernel and user space causing a doublefetch bug, which is a field that has received little research attention. In our work, we first analyzed real-world doublefetch bug cases and extracted two specific patterns for doublefetch bugs. Based on these patter ns, we proposed an approach of multi-taint parallel tracking to detect double-fetch bugs. We also implemented a prototype called DFTracker (doublefetch bug tracker), and we evaluated it with our test suite. Our experiments demonstrated that it could effectively find all the double-fetch bugs in the test suite including eight realworld cases with no false negatives and minor false positives. In addition, we tested it on Linux kernel and found a new double-fetch bug. The execution overhead is approximately 2x for single-file cases and approximately 9x for the whole kernel test, which is acceptable. To the best of the authors1 knowledge, this work is the first to introduce multi-taint parallel tracking to double-fetch bug detection—an innovative method that is specific to double-fetch bug features—and has better path coverage as well as lower runtime overhead than the widely used dynamic approaches.

关键词： multi-taint parallel tracking double fetch race condition between kernel and user time of check to time of use real-world case analysis Clang Static Analyzer

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Untrusted Hardware Causes Double-Fetch Problems in the I/O Memory

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Journal of computer Science & Technology 2018年第3期33卷 587-602页

作者： Kai Lu Peng-Fei Wang Gen Li Xu Zhou College of Computer National University of Defense Technology Changsha 410073 China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha 410073 China Collaborative Innovation Center of High-Performance Computing National University of Defense Technology Changsha 410073 China

The double fetch problem occurs when the data is maliciously changed between two kernel reads of the supposedly same data, which can cause serious security problems in the kernel. Previous research focused on the double fetches between the kernel and user applications. In this paper, we present the first dedicated study of the double fetch problem between the kernel and peripheral devices （aka. the hardware double fetch）. Operating systems communicate with peripheral devices by reading from and writing to the device mapped I/O （input and output） memory. Owing to the lack of effective validation of the attached hardware, compromised hardware could flip the data between two reads of the same I/O memory address, causing a double fetch problem. We propose a static pattern-matching approach to identify the hardware double fetches from the Linux kernel. Our approach can analyze the entire kernel without relying on the corresponding hardware. The results are categorized and each category is analyzed using case studies to discuss the possibility of causing bugs. We also find four previously unknown double-fetch vulnerabilities, which have been confirmed and fixed after reporting them to the maintainers.

关键词： hardware double fetch double-fetch bug I/O memory peripheral device double-fetch vulnerability

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Identifying repeated interleavings to improve the efficiency of concurrency bug detection 15th

Identifying repeated interleavings to improve the efficiency...

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15th International Conference on Algorithms and Architectures for parallel processing, ICA3PP 2015

作者： Wu, Zhendong Lu, Kai Wang, Xiaoping Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha410073 China

ISBN: (纸本)9783319271392

Detecting concurrency bugs is becoming increasingly important. Many pattern-based concurrency bug detectors focus on the specific types of interleavings that are correlated to concurrency bugs. To detect multiple types of concurrency bugs, general detectors focus on multiple types of interleaving patterns, including data race pattern, atomicity violation pattern, and atomic-set violation pattern. Unfortunately, they suffer from redundant analysis due to repeated interleavings, which may affect the efficiency of concurrency bug detection. Hence, we propose an approach to identify the repeated interleavings. To the best of our knowledge, this is the first approach that can prune repeated interleavings to improve the efficiency of concurrency bug detection. We apply our approach to existing general detectors (PECAN and Maple) to avoid analyzing repeated interleavings. We evaluated the general detectors with and without our approach, respectively. The experimental results show that the bug detection results are not affected. With our approach, the bug detection time of PECAN and Maple are reduced by 40.0% and 44.4%, respectively. Additionally, our approach does not affect the overhead of bug detection, and consumes only a little memory. © Springer International Publishing Switzerland 2015.

关键词： Efficiency

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A distributed topology-aware overlays construction algorithm 08

A distributed topology-aware overlays construction algorithm

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15th ACM Mardi Gras Conference, MG '08

作者： Zhang, Xiaoming Li, Zhoujun Wang, Yijie School of Computer Science and Engineering Beihang University Beijing 100083 China National Laboratory for Parallel and Distributed Processing NUDT Changsha 410073 China

ISBN: (纸本)9781595938350

Peer-to-Peer (P2P) computing systems are rapidly growing in importance as the medium of choice for the mass storage. Peers in the most P2P systems randomly choose logical neighbors without any knowledge about underlying physical topology. This mechanism can cause a serious topology mismatch between the P2P overlay network and the underlying network. It greatly limits the performance gain from various search or routing techniques. In this paper, a distributed topology-aware overlays construction algorithm Taonet is proposed, in which the overlay network construction is based on the location information of underlying topology. The nodes that are close in the logical network are also close in terms of network latency. This leads to low latency stretch of the overlay network. This algorithm is scalable and distributed. Simulation results indicate that the latency of data location in these topology-aware P2P systems that are constructed with Taonet can be significantly decreased. Copyright © 2008 ACM.

关键词： Overlay networks

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A malicious code detection method based on statistical analysis

A malicious code detection method based on statistical analy...

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2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012

作者： Wu, Yunlong Chen, Chen Wang, Huiquan Zhou, Jie Xu, Xinhai National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha Hunan 410073 China School of Computer National University of Defense Technology Changsha Hunan 410073 China

ISBN: (纸本)9781467300223

The malicious code detection based on behaviors has proved effective. But there are high false positives and high false negatives when using this method. Because the behaviors are always out-of-order and redundant. To solve these problems, this paper proposes a detection method based on statistical analysis. Firstly, this method uses association rules to sort out the behaviors, and then we can get the integrated and accurate behavior sequences. Secondly, by using the association algorithm we can pick up the signatures of behavior sequences. In addition, this method can detect the signatures to judge the threat based on statistical analysis. Experimental results indicate that it can reduce both the false positives and the false negatives effectively. © 2012 IEEE.

关键词： Statistical methods

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