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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Zhenliang Guo Zhen Huang Yong Dou Xiubin Yu Sijie Wang Zhongwu Chen Xinxin Su Xiaohang Liu National Key Laboratory of Parallel and Distributed Processing National University of Defense Technology Changsha China

Discourse structure analysis has shown to be useful for many artificial intelligence (AI) tasks such as text sum-marization and text categorization. However, for the Chinese news domain, the discourse structure analysis system is still immature due to the limitation of the lack of expert-annotated datasets. In this paper, we present CNA, a Chinese news corpus containing 1155 news articles annotated by human experts, which covers four domains and four news media sources. Next, we implement several text classification methods as baselines. Experimental results demonstrate that document-level method can achieve a better performance, and we further propose a document-level neural network model with multiple sentence features which achieves the state-of-the-art performance. In the end, we analyze the content type distribution of each sentence in CNA and the prediction errors of our model that occurred on the test set. The codes and dataset will be open-sourced at https://***/gzl98/Chinese_Discourse_Profiling.

关键词： Analytical models Codes Text categorization Neural networks Predictive models Media Artificial intelligence

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Ruan Jian Xue Bao/Journal of Software 2011年第1期22卷 132-148页

作者： Li, Hui-Ba Tian, Tian Peng, Yu-Xing Li, Dong-Sheng Lu, Xi-Cheng National Laboratory for Parallel and Distributed Computing Computer School National University of Defense Technology Changsha 410073 China Institute of Software Computer School National University of Defense Technology Changsha 410073 China

The Internet has become a vital information infrastructure for modern society. However, the concurrent nature of network introduces a wide-range of difficulties in traditional programming methodology in developing high-quality network programs that significantly reduce productivity. The influence of concurrency on the complexity of software development is comparable to the "concurrency crisis" of software brought by multi-core processors, but it receives much less attention here than what it deserves. There is no universal approach to cope with this issue, and there are even disagreements between different approaches. In this paper, the basic concurrency models and their implementations are introduced, and then the paper surveys the inherent complexities of these approaches, comparing their advantages and disadvantages. Finally, this paper offers an opinion on the possibilities for future research on this topic. © Copyright 2011, Institute of Software, the Chinese Academy of Sciences. All rights reserved.

关键词： Complex networks

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Cloudroid: A cloud framework for transparent and QoS-aware robotic computation outsourcing

arXiv

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arXiv 2017年

作者： Hu, Ben Wang, Huaimin Zhang, Pengfei Ding, Bo Che, Huimin National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology 410073 China

Many robotic tasks require heavy computation, which can easily exceed the robot's onboard computer capability. A promising solution to address this challenge is outsourcing the computation to the cloud. However, exploiting the potential of cloud resources in robotic software is difficult, because it involves complex code modification and extensive (re)configuration procedures. Moreover, quality of service (QoS) such as timeliness, which is critical to robot's behavior, have to be considered. In this paper, we propose a transparent and QoS-aware software framework called Cloudroid for cloud robotic applications. This framework supports direct deployment of existing robotic software packages to the cloud, transparently transforming them into Internet-accessible cloud services. And with the automatically generated service stubs, robotic applications can outsource their computation to the cloud without any code modification. Furthermore, the robot and the cloud can cooperate to maintain the specific QoS property such as request response time, even in a highly dynamic and resource-competitive environment. We evaluated Cloudroid based on a group of typical robotic scenarios and a set of software packages widely adopted in real-world robot practices. Results show that robots capability can be enhanced significantly without code modification and specific QoS objectives can be guaranteed. In certain tasks, the"cloud + robot" setup shows improved performance in orders of magnitude compared with the robot native setup. Copyright © 2017, The Authors. All rights reserved.

关键词： Quality of service

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A distributed Multi-Storage Resource Architecture and I/O Performance Prediction for Scientific computing

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Cluster computing 2003年第3期6卷 189-200页

作者： Shen, X. Choudhary, A. Matarazzo, C. Sinha, P. Center for Parallel and Distributed Computing Department of Electrical and Computer Engineering Northwestern University Evanston USA Lawrence Livermore National Laboratory Livermore USA

I/O intensive applications have posed great challenges to computational scientists. A major problem of these applications is that users have to sacrifice performance requirements in order to satisfy storage capacity requirements in a conventional computing environment. Further performance improvement is impeded by the physical nature of these storage media even when state-of-the-art I/O optimizations are employed. In this paper, we present a distributed multi-storage resource architecture, which can satisfy both performance and capacity requirements by employing multiple storage resources. Compared to a traditional single storage resource architecture, our architecture provides a more flexible and reliable computing environment. This architecture can bring new opportunities for high performance computing as well as inherit state-of-the-art I/O optimization approaches that have already been developed. It provides application users with high-performance storage access even when they do not have the availability of a single large local storage archive at their disposal. We also develop an Application Programming Interface (API) that provides transparent management and access to various storage resources in our computing environment. Since I/O usually dominates the performance in I/O intensive applications, we establish an I/O performance prediction mechanism which consists of a performance database and a prediction algorithm to help users better evaluate and schedule their applications. A tool is also developed to help users automatically generate performance data stored in databases. The experiments show that our multi-storage resource architecture is a promising platform for high performance distributed computing.

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Jammer Localization for Wireless Sensor Networks

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Chinese Journal of Electronics 2023年第4期20卷 735-738页

作者： SUN Yanqiang WANG Xiaodong ZHOU Xingming National Key Laboratory for Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha China

Jamming attack can severely affect the performance of Wireless sensor networks (WSNs) due to the broadcast nature of wireless medium. In order to localize the source of the attacker, we in this paper propose a jammer localization algorithm named as Minimum-circle-covering based localization (MCCL). Comparing with the existing solutions that rely on the wireless propagation parameters, MCCL only depends on the location information of sensor nodes at the border of the jammed region. MCCL uses the plane geometry knowledge, especially the minimum circle covering technique, to form an approximate jammed region, and hence the center of the jammed region is treated as the estimated position of the jammer. Simulation results showed that MCCL is able to achieve higher accuracy than other existing solutions in terms of jammer's transmission range and sensitivity to nodes' density.

关键词： Location awareness Wireless communication Geometry Wireless sensor networks Sensitivity Simulation Jamming

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DMSA: Decentralized and Multi-keyword Selective Data Sharing and Acquisition

DMSA: Decentralized and Multi-keyword Selective Data Sharing...

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International Symposium on parallel and distributed Processing with Applications, ISPA

作者： Moheng Lin Peichang Shi Xiang Fu Feng Jiang Guodong Yi National Key Laboratory of Parallel and Distributed Computing College of Computer Science National University of Defense Technology Changsha China Xiangjiang Lab Changsha China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Blockchain technology has been extensively uti-lized in decentralized data-sharing applications, with the immutability of blockchain providing a witness for the circulation of data. However, current blockchain data-sharing solutions still fail to address the simultaneous screening needs of both the sender and receiver with multi-keywords. Without the capability to support bilateral simultaneous filtering, the disclosure of reasons for matching failures could inadvertently expose sensitive user data. Therefore, the challenge lies in enabling ciphertexts with multiple keywords and receivers with multiple interests to achieve mutual and simultaneous matching. Based on the technical foundations of SE (Searchable Encryption), MABE (Multi-Attribute Based Encryption), and polynomial fitting, this paper proposes a scheme called DMSA (Decentralized and Multi-keyword selective Sharing and selective Acquisition). This scheme can satisfy soundness, enabling ciphertexts carrying multiple keywords and receivers representing multiple interests to match each other simultaneously. We conducted a security analysis that confirms the security of DMSA against chosen-plaintext attacks. Our experimental results demonstrate a significant efficiency improvement, with a 67% increase over single-keyword data-sharing schemes and a 16% enhancement compared to the existing multi-keyword data-sharing solution.

关键词： distributed processing Filtering Data security keyword search Fitting Receivers Polynomials Data models Blockchains Encryption

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Security issues and solutions in cloud computing

Security issues and solutions in cloud computing

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32nd IEEE International Conference on distributed computing Systems Workshops, ICDCSW 2012

作者： You, Pengfei Peng, Yuxing Liu, Weidong Xue, Shoufu National Key Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha China Jiangsu Automation Research Institute Jiangsu China Air Defense Forces Academy CPLA Zhengzhou Henan China

ISBN: (纸本)9781467314237

Recently, Cloud computing, as one of the hottest words in IT world, has drawn great attention. Many IT companies such as IBM, Google, Amazon, Microsoft, Yahoo and others vigorously develop cloud computing systems and related products to customers. However, there are still some difficulties for customers to adopt cloud computing, in which many security issues exist, because data for a customer is stored and processed in cloud, not in a local machine. This paper briefly introduces cloud computing and its key concepts. In particularly, we intend to discuss security requirements and security issues involving data, application and virtualization in cloud computing, as well as current solutions to these issues. © 2012 IEEE.

关键词： Virtualization

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parallel Accelerating Ultra-Long Read Alignment by Vertical Partitioning Data

Parallel Accelerating Ultra-Long Read Alignment by Vertical ...

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International Symposium on parallel Architectures, Algorithms and Programming (PAAP)

作者： Deng Pan Cheng Zhong Danyang Chen Jinxiong Zhang Feng Yang School of Computer Electronics and Information Key Laboratory of Parallel Distributed Computing Technology in Guangxi Universities Guangxi University Nanning Guangxi China School of Computer Electronics and Information Key Laboratory of Parallel Distributed Computing Guangxi University Nanning Guangxi China

ISBN: (纸本)9781665452199

The alignment between sequencing reads and genome is a basic work in biological big data analysis. Each read of the third generation sequencing data is getting longer, and the data size is getting larger. To effectively solve the ultra-long read alignment problem with high requirements for computing and memory capacity, a strategy for vertical partitioning ultra-long reads on hybrid CPU/GPU cluster is proposed, and a heap data structure is used to filter the local aligned results in all computing nodes of the parallel cluster system according to the alignment score to reduce the data transmission size. The methods for early termination and parallel merging-splicing are used to accelerate splicing local aligned results. The local aligned results among all computing nodes are collected and extended to obtain the final alignment results. The experimental results on datasets of simulated and real ultra-long reads show that the proposed parallel alignment algorithm can obtain high alignment accuracy, sensitivity and base-level sensitivity as a whole, and accelerate completing alignment between ultra-long reads and reference genome.

关键词： Sequential analysis Sensitivity Splicing Merging Memory management Genomics Programming

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Human motion recognition by three-view kinect sensors in virtual basketball training

Human motion recognition by three-view kinect sensors in vir...

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2020 IEEE Region 10 Conference, TENCON 2020

作者： Yao, Baoqi Gao, Hui Su, Xin Beijing University of Posts and Telecommunications Key Laboratory of Trustworthy Distributed Computing and Service China Tsinghua University Beijing National Research Center for Information Science and Technology Beijing China

ISBN: (纸本)9781728184555

In recent years, human action recognition has received a considerable amount of research attention because of it's potential in a variety of applications, such as video surveillance, human-computer interaction, and virtual reality (VR). However, many researches on human action recognition performed in single-camera or double-camera system, which achieve reduced performance due to vulnerability to partial occlusion and miss-recognition of back. Some works on human action recognition use multiple cameras but are too complex for practical application. In this paper, we propose a new human action recognition system using triple Kinect sensors for VR application. Particularly, we design a mark detection method to determine the front of user and fusion skeleton data in real time. Features are extracted from three-dimensional (3D) skeleton data sequences, and divided into five parts according to body parts. A classification model based on the part-aware long short-term memory networks is proposed to recognize human motion. Finally, we demonstrate the system with a virtual reality basketball application and the results of experiment validate the feasibility of the proposed system. © 2020 IEEE.

关键词： Virtual reality

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Efficient and available in-memory KV-store with hybrid erasure coding and replication 16

Efficient and available in-memory KV-store with hybrid erasu...

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Proceedings of the 14th Usenix Conference on File and Storage Technologies

作者： Heng Zhang Mingkai Dong Haibo Chen Shanghai Key Laboratory of Scalable Computing and Systems Institute of Parallel and Distributed Systems Shanghai Jiao Tong University

ISBN: (纸本)9781931971287

In-memory key/value store (KV-store) is a key building block for many systems like databases and large websites. Two key requirements for such systems are efficiency and availability, which demand a KV-store to continuously handle millions of requests per second. A common approach to availability is using replication such as primary-backup (PBR), which, however, requires M + 1 times memory to tolerate M failures. This renders scarce memory unable to handle useful user *** paper makes the first case of building highly available in-memory KV-store by integrating erasure coding to achieve memory efficiency, while not notably degrading performance. A main challenge is that an in-memory KV-store has much scattered metadata. A single KV put may cause excessive coding operations and parity updates due to numerous small updates to metadata. Our approach, namely Cocytus, addresses this challenge by using a hybrid scheme that leverages PBR for small-sized and scattered data (e.g., metadata and key), while only applying erasure coding to relatively large data (e.g., value). To mitigate well-known issues like lengthy recovery of erasure coding, Cocytus uses an online recovery scheme by leveraging the replicated metadata information to continuously serving KV requests. We have applied Cocytus to Memcached. Evaluation using YCSB with different KV configurations shows that Cocytus incurs low overhead for latency and throughput, can tolerate node failures with fast online recovery, yet saves 33% to 46% memory compared to PBR when tolerating two failures.

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