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Overview of blockchain consensus mechanism 2020

Overview of blockchain consensus mechanism

引用

2nd International Conference on Big Data Engineering, BDE 2020

作者： Zhang, Changqiang Wu, Cangshuai Wang, Xinyi Key Laboratory of Parallel and Distributed Computing College of Computer National University of Defense Technology China College of Computer National University of Defense Technology China

ISBN: (纸本)9781450377225

The advent of the Bitcoin system has brought another boom in the Internet era. In a very short time, many Blockchain systems come into being successively, whose decentration, consensus mechanisms, intelligent contract, and other characteristics make them applicable to various fields such as finance, education, medical, technology, etc. The consensus mechanism is the core of Blockchain technology. And a good consensus mechanism plays a very important role in the stable operation of the Blockchain system. The continuous improvement of consensus mechanisms such as PoW (proof-of-work), PoS (proof-of-stake), DPoS (delegated-proof-of-stake), and PBFT (Practical Byzantine Fault Tolerance) has led to the evolution of Blockchain technology to Blockchain 3.0. Starting from the issue of Byzantine generals, this article analyzes common consensus mechanisms based on existing Blockchain applications and then evaluates their consistency. This paper has a unique perspective, selection and comment on the latest progress and important literature in the field of block chain. At last, it also has a high degree of summary and prospect to the existing problems and the future development trend. © 2020 ACM.

关键词： Blockchain

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A novel rough set approach for classification

A novel rough set approach for classification

引用

2006 IEEE International Conference on Granular Computing

作者： Zhang, Li-Juan Li, Zhou-Jun National Laboratory for Parallel and Distributed Processing Changsha 410073 China School of Computer Science and Engineering Beihang University Beijing 100083 China

ISBN: (纸本)1424401348

Rough set theory has been widely and successfully used in data mining, especially in classification field. But most existing rough set based classification approaches require computing optimal attribute reduction, which is usually intractable and many problems related to it have been shown to be NT-hard. Although approximate algorithms exist, they also tend to be computationally expensive. This paper presents a novel rough set method for classification, which does not require computing attribute reduction. It stepwise investigates condition attributes and outputs the classification rules induced by them, which is just like the strategy of "on the fly". The theoretical analysis and the empirical study show that the proposed method is effective and efficient. © 2006 IEEE.

关键词： Rough set theory

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An efficient two-level bitmap index for cloud data management

An efficient two-level bitmap index for cloud data managemen...

引用

2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011

作者： Bin, Huang Yu-Xing, Peng School of Computer Science Wuhan University Wuhan China National Laboratory of Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha China

ISBN: (纸本)9781612844855

A Cloud may be seen as a type of flexible computing infrastructure consisting of many compute nodes, where resizable computing capacities can be provided to different customers. To fully harness the power of the Cloud, efficient data management is needed to handle huge volumes of data and support a large number of concurrent end users. To achieve that, a scalable and high-throughput indexing scheme is generally required. Such an indexing scheme must support parallel search to improve scalability. In this paper, we present a bitmap based indexing scheme for efficient data processing in the Cloud. Our approach can be summarized as follows. First, we build a local bitmap index for each compute node which only indexes data residing on the node. Second, we organize the compute nodes as a structured overlay and each node maintains a portion of the global index for the whole different data. The global index is also bitmap index to indicate the node each data resides in. Third, all bitmaps are compressed by adopting run-length coding for reducing storage requirement. We conduct extensive experiments on a LAN, and the results demonstrate that our indexing scheme is dynamic, efficient and scalable. © 2011 IEEE.

关键词： Information management

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Simulation research of communication networks based on prim algorithm

Simulation research of communication networks based on prim ...

引用

International Forum on Information Technology and Applications

作者： Yang, Chenghui Ren, ChuanJun College of Electrical Engineering Northwest University for Nationalities Lanzhou 730030 China National Laboratory for Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha 410073 China

ISBN: (纸本)9780769541150

In order to improve the efficiency of the communication networks, we used the Kruskal algorithm and the Prim algorithm through algorithm comparison and analysis methods of data structure. A dynamic framework for the communication network installed system is built. Moreover, according to the actual framework of the communication network specific issues, the module chooses the Minimum Cost Spanning Tree Prim algorithm ultimately. The assumptions process and outcomes simulation have proper analysis and certification by C language. Experimental results show that the Minimum Cost Spanning Tree of Prim algorithm on the installed system for communication networks dynamic planning process have the advantage of speed and effectively reduce the waste of resources, which not only can ensure efficiency but also can effectively improve communication networks installed cost. © 2010 IEEE.

关键词： Costs

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High-performance Network Traffic Classification Based on Graph Neural Network 6

High-performance Network Traffic Classification Based on Gra...

引用

6th IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2023

作者： Pang, Bo Fu, Yongquan Ren, Siyuan Jia, Yan Harbin Institute of Technology College of Computer Science and Technology Shenzhen China National University of Defense Technology National Key Laboratory for Parallel and Distributed Processing College of Computer Changsha China Peng Cheng Laboratory Shen Zhen China

ISBN: (纸本)9781665460033

Network traffic classification is crucial for network security and network management and is one of the most important network tasks. Current state-of-the-art traffic classifiers are based on deep learning models to automatically extract features from packet streams. Unfortunately, current approaches fail to effectively combine the structural information of traffic packets with the content features of the packets, resulting in limited classification accuracy. In this paper, we propose a graph neural network model for network traffic classification, which can well perceive the interaction feature of packets in traffic. Firstly, we design a graph structure for packets' flows to hold the interaction information between packets, which embeds both packet contents and sequence relationships into a unified graph. Secondly, we propose a graph neural network framework for graph classification to automatically learn the structural features of the packets' flows together with the packets' features. Extensive evaluation results on real-world traffic data show that the proposed model improves the prediction accuracy of improves the prediction accuracy by 2% to 37% for malicious traffic classification. © 2023 IEEE.

关键词： Graph neural networks

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Efficient social network approximate analysis on blogosphere based on network structure characteristics

Efficient social network approximate analysis on blogosphere...

引用

3rd Workshop on Social Network Mining and Analysis, SNA-KDD '09

作者： Tang, Jintao Wang, Ting Wang, Ji Wei, Dengping School of Computer National University of Defense Technology ChangSha Hunan 410073 China National Laboratory for Parallel and Distributed Processing ChangSha Hunan 410073 China

ISBN: (纸本)9781605586762

As a typical social media in Web 2.0, blogs have attracted a surge of researches. Unlike the traditional studies, the social networks mined from Internet are very large, which makes a lot of social network analyzing algorithms to be intractable. According to this phenomenon, this paper addresses the novel problem of efficient social networks analyzing on blogs. This paper turns to account the structural characteristics of real large-scale complex networks, and proposes a novel shortest path approximate algorithm to calculate the distance and shortest path between nodes efficiently. The approximate algorithm then is incorporated with social network analysis algorithms and measurements for large-scale social networks analysis. We illustrate the advantages of the approximate analysis through the centrality measurements and community mining algorithms. The experiments demonstrate the effectiveness of the proposed algorithms on blogs, which indicates the necessity of taking account of the structural characteristics of complex networks when optimizing the analysis algorithms on large-scale social networks. Copyright 2009 ACM.

关键词： Blogs

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Reducing repair traffic in P2P backup systems: Exact regenerating codes on hierarchical codes

Reducing repair traffic in P2P backup systems: Exact regener...

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作者： Huang, Zhen Biersack, Ernst Peng, Yuxing Department of Computer National Laboratory of Parallel and Distributed Processing National University of Defense Technology Changsha Hunan 410073 China Eurecom Sophia Antipolis France

Peer to peer backup systems store data on "unreliable" peers that can leave the system at any moment. In this case, the only way to assure durability of the data is to add redundancy using either replication or erasure codes. Erasure codes are able to provide the same reliability as replication requiring much less storage space. Erasure coding breaks the data into blocks that are encoded and then stored on different nodes. However, when storage nodes permanently abandon the system, new redundant blocks must be created, which is referred to as repair. For "classical" erasure codes, generating a new block requires the transmission of k blocks over the network, resulting in a high repair traffic. Recently, two new classes of erasure codes, Regenerating Codes and Hierarchical Codes, have been proposed that significantly reduce the repair traffic. Regenerating Codes reduce the amount of data uploaded by each peer involved in the repair, while Hierarchical Codes reduce the number of nodes participating in the repair. In this article we propose to combine these two codes to devise a new class of erasure codes called ER-Hierarchical Codes that combine the advantages of both. © 2011 ACM.

关键词： Repair

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An efficient packing algorithm for spatial keyword queries

An efficient packing algorithm for spatial keyword queries

引用

6th International Conference on Convergence and Hybrid Information Technology, ICHIT 2012

作者： Pan, Jinkun Li, Dongsheng Li, Liming National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology 410073 Changsha China Shanghai Garrision 200040 Shanghai China

ISBN: (纸本)9783642326448

With the increase of location-based services, Web contents are being geo-tagged, and spatial keyword queries that retrieve objects satisfying both spatial and keyword conditions are gaining in prevalence. Unfortunately, the state-of-the-art packing algorithms only focus on spatial relationship, and they are not fit for the spatial keyword queries. In this paper, we propose a new packing algorithm named KBS which takes both location and keyword information into consideration, thus optimizing R-tree for spatial keyword queries. Experimental results on both real and synthetic datasets show that our method achieves high performance and space utilization. © 2012 Springer-Verlag.

关键词： Location based services

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Minimum redundancy gene selection based on grey relational analysis

Minimum redundancy gene selection based on grey relational a...

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作者： Zhang, Li-Juan Li, Zhou-Jun Chen, Huo-Wang Wen, Jian National Laboratory for Parallel and Distributed Processing Changsha 410073 China School of Computer Science and Engineering Beihang University Beijing 100083 China

ISBN: (纸本)0769527027

In this article we describe a method for selecting informative genes from microarray data. The method is based on clustering, namely, it first find similar genes, group them and then select informative genes from these groups to avoid redundancy. A new gene similarity measure based on Grey Relational Analysis (GRA), called Grey Relational Grade (GRG), is used in clustering. Experiments on three public data sets demonstrate the effectiveness of our method. © 2006 IEEE.

关键词： Redundancy

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Character feature learning for named entity recognition

Character feature learning for named entity recognition

引用

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

The deep neural named entity recognition model automatically learns and extracts the features of entities and solves the problem of the traditional model relying heavily on complex feature engineering and obscure professional knowledge. This issue has become a hot topic in recent years. Existing deep neural models only involve simple character learning and extraction methods, which limit their capability. To further explore the performance of deep neural models, we propose two character feature learning models based on convolution neural network and long short-term memory network. These two models consider the local semantic and position features of word characters. Experiments conducted on the CoNLL-2003 dataset show that the proposed models outperform traditional ones and demonstrate excellent performance. © Copyright 2018 The Institute of Electronics Information and Communication Engineers.

关键词： Extraction

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