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1st International Conference on Networking and distributed computing, ICNDC 2010

作者： Kuang, Xiao-Hui Huang, Min-Huan Che, Yong-Gang Jin, Li Fei, Xu National Key Laboratory of Science and Technology on Information System Security Beijing Institute of System and Engineering Beijing China Department of Computer Science and Technology Tsinghua University Beijing China National Laboratory for Parallel and Distributed Process National University of Defense Technology Changsha China

ISBN: (纸本)9780769542072

Network emulation environment is great importance to the research of network protocols, applications and security mechanism. Large-scale network topology generation is one of key technologies to construct network emulation environment. In this paper, a new large-scale network topology generation framework called LSNTGF is proposed, which divides the network topology into three hierarchies: AS, router and terminal node. It contains the assignment mechanism to bandwidth of each link and IP address of each node. The framework is evaluate by implementation, and the result illustrate it is efficient to network emulation environment for network protocols and security research. © 2010 IEEE.

关键词： Network topology

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XGrad: Boosting Gradient-Based Optimizers With Weight Prediction

arXiv

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arXiv 2023年

作者： Guan, Lei Li, Dongsheng Shi, Yanqi Meng, Jian The Department of Mathematics National University of Defense Technology Changsha China The National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology China

In this paper, we propose a general deep learning training framework XGrad which introduces weight prediction into the popular gradient-based optimizers to boost their convergence and generalization when training the deep neural network (DNN) models. In particular, ahead of each mini-batch training, the future weights are predicted according to the update rule of the used optimizer and are then applied to both the forward pass and backward propagation. In this way, during the whole training period, the optimizer always utilizes the gradients w.r.t. the future weights to update the DNN parameters, making the gradient-based optimizer achieve better convergence and generalization compared to the original optimizer without weight prediction. XGrad is rather straightforward to implement yet pretty effective in boosting the convergence of gradient-based optimizers and the accuracy of DNN models. Empirical results concerning five popular optimizers including SGD with momentum, Adam, AdamW, AdaBelief, and AdaM3 demonstrate the effectiveness of our proposal. The experimental results validate that XGrad can attain higher model accuracy than the baseline optimizers when training the DNN models. The code of XGrad will be available at: https://***/guanleics/XGrad. Copyright © 2023, The Authors. All rights reserved.

关键词： Forecasting

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TeeSwap: Private Data Exchange using Smart Contract and Trusted Execution Environment 23

TeeSwap: Private Data Exchange using Smart Contract and Trus...

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23rd IEEE International Conference on High Performance computing and Communications, 7th IEEE International Conference on Data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Chen, Peng Shi, Peichang Xu, Jie Fu, Xiang Li, Linhui Zhong, Tao Xiang, Liangliang Kong, Jinzhu College of Computer National University of Defense Technology National Key Laboratory of Parallel and Distributed Processing Changsha410073 China Zhejiang Lab Hangzhou311100 China Kylin Software Co. Ltd Changsha410073 China

ISBN: (纸本)9781665494571

With importance of data value is approved, data-sharing will create more and greater value has become consensus. However, data exchange has to use a trusted third party(TTP) as an intermediary in an untrusted network environment, which may lead to leakage of data privacy. In this paper, we design a system named TeeSwap, which uses smart contract to complete data exchange, and at the same time uses cryptographic algorithms and trusted execution environment (TEE) to ensure privacy in process of data transmission, verification and contract execution. Meanwhile, TeeSwap can ensure the credibility, fairness, integrity and privacy while data are shared in our system. In the end, we implement contracts about data market and data exchange. When confirming the data transaction, data market contract can automatically generate and deploy exchange contract, which can complete the data exchange authoritatively. © 2021 IEEE.

关键词： Data privacy Smart contracts Data communication Cryptography

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Cooperative monitoring BGP among autonomous systems

引用

Security and Communication Networks 2015年第10期8卷 1943-1957页

作者： Hu, Ning Wang, BaoSheng Liu, Xin National Key Laboratory for Parallel and Distributed Processing College of Computer National University of Defense Technology Changsha Hunan China

As the de facto Internet inter-domain routing protocol, BGP protocol has a number of vulnerabilities and weakness. Monitoring BGP is an effective way to improve the security of inter-domain routing. This paper presents a cooperative BGP monitoring method, which is called cooperative information sharing model (CoISM). CoISM is based on self-organization and can be used to solve some problems during BGP monitoring, such as route validation and bogus route notification delivery. CoISM provides autonomous systems with a more comprehensive information view by introducing information diffuse reflection based on initiative inquiry and making use of the relativity of monitoring information. CoISM optimizes the information transmission by leveraging the data locality caused by BGP policy and implements ISP coordination with low communication and deployment cost. More specifically, CoISM provides a self-organizing and incentive mechanism, which drives autonomous systems to coordinate independently and shares information on-demand. CoISM supports incremental deployment and can also be applied to a wide range of inter-domain cooperative management applications such as inter-domain routing failure analysis and intrusion detection. © 2014 John Wiley & Sons, Ltd.

关键词： Monitoring

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Meta-Tsallis-Entropy Minimization: A New Self-Training Approach for Domain Adaptation on Text Classification

arXiv

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arXiv 2023年

作者： Lu, Menglong Huang, Zhen Tian, Zhiliang Zhao, Yunxiang Fei, Xuanyu Li, Dongsheng National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology China Beijing Institute of Biotechnology China Suiren Information China

Text classification is a fundamental task for natural language processing, and adapting text classification models across domains has broad applications. Self-training generates pseudo-examples from the model’s predictions and iteratively train on the pseudo-examples, i.e., mininizes the loss on the source domain and the Gibbs entropy on the target domain. However, Gibbs entropy is sensitive to prediction errors, and thus, self-training tends to fail when the domain shift is large. In this paper, we propose Meta-Tsallis Entropy minimization (MTEM), which applies meta-learning algorithm to optimize the instance adaptive Tsallis entropy on the target domain. To reduce the computation cost of MTEM, we propose an approximation technique to approximate the Second-order derivation involved in the meta-learning. To efficiently generate pseudo labels, we propose an annealing sampling mechanism for exploring the model’s prediction probability. Theoretically, we prove the convergence of the meta-learning algorithm in MTEM and analyze the effectiveness of MTEM in achieving domain adaptation. Experimentally, MTEM improves the adaptation performance of BERT with an average of 4 percent on the benchmark dataset. © 2023, CC BY-NC-SA.

关键词： Learning algorithms

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MCHITS: Monte carlo based method for hyperlink induced topic search on networks

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Journal of Networks 2013年第10期8卷 2376-2382页

作者： Jin, Zhaoyan Shi, Dianxi Wu, Quanyuan Fan, Hua National Key Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha 410073 China

Hyperlink Induced Topic Search (HITS) is the most authoritative and most widely used personalized ranking algorithm on networks. The HITS algorithm ranks nodes on networks according to power iteration, and has high complexity of computation. This paper models the HITS algorithm with the Monte Carlo method, and proposes Monte Carlo based algorithms for the HITS computation. Theoretical analysis and experiments show that the Monte Carlo based approximate computing of the HITS ranking reduces computing resources a lot while keeping higher accuracy, and is significantly better than related works. © 2013 ACADEMY PUBLISHER.

关键词： Monte Carlo methods

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CNA: A Dataset for Parsing Discourse Structure on Chinese News Articles

CNA: A Dataset for Parsing Discourse Structure on Chinese Ne...

引用

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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Cooperative Air-Ground Instant Delivery by UAVs and Crowdsourced Taxis 40

Cooperative Air-Ground Instant Delivery by UAVs and Crowdsou...

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40th IEEE International Conference on Data Engineering, ICDE 2024

作者： Gao, Junhui Wang, Qianru Zhang, Xin Shi, Juan Zhao, Xiang Han, Qingye Pan, Yan School of Computer Science Northwestern Polytechnical University China School of Computer Science and Technology Xidian University China Air Force Engineering University China National University of Defense Technology Laboratory for Big Data and Decision China School of Management Science and Real Estate Chongqing University China National University of Defense Technology National Key Laboratory of Information Systems Engineering China National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing China

ISBN: (纸本)9798350317152

Instant delivery has become a fundamental service in people's daily lives. Different from the traditional express service, the instant delivery has a strict shipping time constraint after being ordered. However, the labor shortage makes it challenging to realize efficient instant delivery. To tackle the problem, researchers have studied to introduce vehicles (i.e., taxis) or Unmanned Aerial Vehicles (UAVs or drones) into instant delivery tasks. Unfortunately, the delivery detour of taxis and the limited battery of UAVs make it hard to meet the rapidly increasing instant delivery demands. Under this circumstance, this paper proposes an air-ground cooperative instant delivery paradigm to maximize the delivery performance and meanwhile minimize the negative effects on the taxi passengers. Specifically, a data-driven delivery potential-demands-aware cooperative strategy is designed to improve the overall delivery performance of both UAVs and taxis as well as the taxi passengers' experience. The experimental results show that the proposed method improves the delivery number by 30.1% and 114.5% compared to the taxi-based and UAV-based instant delivery respectively, and shortens the delivery time by 35.7% compared to the taxi-based instant delivery. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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

引用

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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