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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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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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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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Algorithm for distributed Constraint Optimization Problems with low constraint density

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Ruan Jian Xue Bao/Journal of Software 2011年第4期22卷 625-639页

作者： Ding, Bo Wang, Huai-Min Shi, Dian-Xi Tang, Yang-Bin School of Computer National University of Defense Technology Changsha 410073 China National Key Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha 410073 China

Many challenges in multi-agent coordination can be modeled as distributed Constraint Optimization Problems (DCOPs). Aiming at DCOPs with low constraint density, this paper proposes a distributed algorithm based on the idea of greed and backjumping. In this algorithm, each agent makes decisions according to the greedy principle that the most assignment combinations in the problems with low constraint density occur at a zero cost, and the backjumping mechanism among the agents ensures the success of this algorithm, even when this greedy principle leads to a local optimum. In contrast with the existing mainstream DCOP algorithms, this algorithm can solve problems with low constraint density with fewer messages while keeping the polynomial message length and space complexity. The correctness of the key mechanisms in this algorithm has been proved, and those advantages in performance have been verified by experiments. © 2011 ISCAS.

关键词： Multi agent systems

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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 computing for large-scale author name disambiguation in medline 21

Parallel computing for large-scale author name disambiguatio...

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21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Tang, Anyao Wu, Chengkun Liu, Jie Wang, Wei Yang, Xi Xing, Yuting Science and Technology on Parallel and Distributed Processing Laboratory Laboratory of Software Engineering for Complex Systems National University of Defense Technology Changsha410073 China State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha410073 China College of Computer National University of Defense Technology Changsha 410073 China

ISBN: (纸本)9781728120584

Author name disambiguation (AND) is an important task in the field of scientific data mining. It has become a great challenge with the rapid growth of academic digital libraries. The task of AND for a large number of authors is computationally intensive. In particular, an author's name in MEDLINE is represented by full last name and initials, like 'Zhang S', which leads to a lot of identical strings that actually represent different names. In this paper, we proposed an efficient algorithm for parallel AND computation. The proposed algorithm mainly addresses the load balancing issue across many computing nodes. It involves the following strategies:(1) Author-based load balancing, which splits the computation load for each core by author name labels. (2) Matrix-based strategy, which calculates the pairwise similarity between publications and saves them in a matrix globally shared by all processes. Then group them by width-first search. We combine the above two strategies, the second of which is used to calculate authors with a large number of documents, and the other authors apply the first. We constructed a publications database written by Chinese authors from MEDLINE, the biggest public database for biomedical literature (abstracts). For benchmark testing, we experimented our algorithm with a dataset of 1 million publications on the Tianhe-2A supercomputer. Firstly, we trained an AND classifier that can achieve 98.1% of F1. The serial computation time is estimated to be approximately 246 hours, while the parallel execution time is approximately 66 hours in the case of four cores on a single node (with a speedup of 3.7x). Finally, we reduced the total parallel computing time of 1 million documents to about 2 hours and achieved 65.8% of parallelism efficiency using 200 cores on 90 nodes. © 2019 IEEE.

关键词： Matrix algebra

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iRank: Supporting Proximity Ranking for Peer-to-Peer Applications

iRank: Supporting Proximity Ranking for Peer-to-Peer Applica...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Yongquan Fu Yijie Wang National Key Laboratory of Parallel and Distributed Processing School of Computer National University of Defense Technology China

Proximity ranking according to end-to-end network distances (e.g., Round-Trip Time, RTT) can reveal detailed proximity information, which is important in network management and performance diagnosis in distributed systems. However, to the best of our knowledge, there has been no similar work on this subject in the P2P computing field. We present a distributed rating method iRank, that enables proximity rankings by providing discrete ratings in a distributed manner. It formulates the proximity ranking as a rating problem that faithfully captures the proximity based on noisy distance measurements scalably and practically. The primary challenge in inferring proximity rankings is enforcing distributed ratings with complex rating policies. Our solution is based on reconstructing ratings by decomposing a centralized rating method Maximum Margin Matrix Factorization (MMMF) into independent sub-problems, that can be efficiently solved in a decentralized manner. By relaxing the dependence on infrastructure nodes that are a single point of failure and limit scalability, iRank can gracefully handle network churns. Through real network latency data sets, we demonstrate that iRank can predict ratings with low distortion, which are smaller than 20 percentage worse than the centralized method, in the context of synthetic complex rating policies.

关键词： Peer to peer computing distributed computing Computer networks Network servers Application software Laboratories distributed processing Concurrent computing Computer network management Conference management

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AUModel:A Conceptual model for Adaptive Software

AUModel:A Conceptual model for Adaptive Software

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2014 IEEE 5th International Conference on Software Engineering and Service Science

作者： Hui Liu Bo Ding Dianxi Shi Huaimin Wang National Key Laboratory for Parallel and Distributed Processing College of Computer ScienceNational University of Defense Technology

Pervasive software should be able to adapt itself to the changing environments and user ***,it will bring great challenges to the software engineering *** paper proposes AUModel,a conceptual model for adaptive software,which takes adaptability as an inherent feature and can act as the foundation of the engineering *** introducing AUModel,the reuse of software adaptation infrastructure as well as the separation of adaptation concerns are enabled,which can facilitate both the development and maintenance of adaptive *** paper also presents our initial attempts to realize this model,including a middleware prototype to support this model and an application to validate its effectiveness.

关键词： pervasive computing adaptive software middleware

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IWFR:Exploiting Full-duplex in Wireless Relay Networks

IWFR:Exploiting Full-duplex in Wireless Relay Networks

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2014 4th IEEE International Conference on Information Science and technology

作者： Yong Lu Shaohe Lv Xiaodong Wang Xingming Zhou National Key Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology

Traditional wireless relay networks have large endto-end time delay and low throughput because of the limit that it can't receive and forward at the same *** this paper,we proposed IWFR:Immediate Wireless Full-Duplex Relay which exploits the advantages of full-duplex to shorten the end-to-end time delay and improve the *** the same time,we designed a new implicit acknowledgement mechanism,which can eliminate the ACK overheads and evidently improve the throughput of the *** implement IWFR,we also modified the full-duplex node architecture to make it support for immediate *** shows that IWFR shortens the end-to-end time delay by 60%on average and improves the throughput to 240%of the original relay.

关键词： Relay IWFR:Exploiting Full-duplex in Wireless Relay Networks

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HyperSpring: Accurate and Stable Latency Estimation in the Hyperbolic Space

HyperSpring: Accurate and Stable Latency Estimation in the H...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Yongquan Fu Yijie Wang National Key Laboratory of Parallel and Distributed Processing School of Computer National University of Defense Technology China

Predicting network latencies between Internet hosts can efficiently support large-scale Internet applications, e.g., file sharing service and the overlay construction. Several study use the hyperbolic space to model the Internet dense-core and many-tendril structure. However, existing hyperbolic space based embedding approaches are not designed for accurate latency estimation in the distributed context. We present HyperSpring, which estimates latency by modelling a mass spring system in the hyperbolic similar with Vivaldi. HyperSpring adopts coordinate initialization to speed up the convergence of coordinate computation, uses multiple-round symmetric updates to escape from bad local minima, and stabilizes coordinates by compensating RTT measurements to reduce the coordinate drifts. Evaluation results based on a network trace of 226 PlanetLab nodes indicate that, compared to Euclidean-space based Vivaldi, hyperspring provides performance improvements for most nodes, and incurs slightly higher distortions for a small number of nodes.

关键词： Delay IP networks Web and internet services Large-scale systems Peer to peer computing Springs Convergence Coordinate measuring machines Distortion measurement Extraterrestrial measurements

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