Algorithm of simulation time synchronization over large-scale nodes

Zhao, Qi; Zhou, Zhong; Fang, Lu

doi:10.1007/s11432-008-0118-x

Cited by 4 publications

(1 citation statement)

References 8 publications

(10 reference statements)

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“…With the rapid development of Internet business in recent years, the research on the extraction of web page commodity information has become a hot spot, and it has rapidly spread to tourism, medicine, agriculture and other fields. The research on web page information extraction involves many fields, and many studies [4][5][6] The text extraction mainly focuses on the information extraction of the semi-structured text of the web pages, but there are not many bibliographic information extraction methods for the characteristics of the semi-structured book web pages. At present, the research work on web page information extraction mainly includes the following aspects:…”

Section: Introductionmentioning

confidence: 99%

Normalized Storage Model Construction and Query Optimization of Book Multi-Source Heterogeneous Massive Data

Wang

Liu

2023

IEEE Access

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According to the characteristics of massive, multi-source, heterogeneous, and rapid growth of book literature data information from the perspective of the metaverse, in order to meet the requirements of efficient management and rapid retrieval such as standardized storage, effective extraction, and scientific library construction for unstructured massive and heterogeneous book in-formation, this study focuses on the normalization of multi-source heterogeneous massive book data, the construction of a warehouse model for book data in the metaverse perspective, and the query and optimization of book data. Systematic research and implementation were conducted to solve the problem of how to process, manage, and query multi-source heterogeneous massive book data in the metaverse, improving the utilization value and query efficiency of the data. This study utilized the semi-structured features of book text data to construct an extraction rule model for heterogeneous book data, and effectively extracted massive heterogeneous book information. Based on the HBase distributed storage structure and parallel computing technology, the storage scheme has been optimized and query efficiency has been improved to ensure efficient management and retrieval of massive heterogeneous book data. The experimental results show that compared with traditional methods, there are significant improvements in multiple aspects such as the accuracy and recall rate of book text data extraction, the management methods and query efficiency of book information.

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Section: Introductionmentioning

confidence: 99%

Normalized Storage Model Construction and Query Optimization of Book Multi-Source Heterogeneous Massive Data

Wang

Liu

2023

IEEE Access

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A Publish/Subscribe based correlative matching method for multi-domain virtual environment

Liu

Chen

2011

2011 IEEE International Symposium on VR Innovation

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The multi-domain virtual environment is an important research area of the distributed virtual reality. However, frequent interaction, great quantity of messages and the discrepant need of each individual simulation domain resulted in numerous redundant messages. In this paper, we propose a Publish/Subscribe based correlative matching method for multidomain virtual environment .This method focus on data filtering of domains' gateways in addition to the DDM scheme. The paper introduces the correlative matching algorithm, the binary representation and the matching method which based on publish/subscribe relationship. Analysis and experiments show that this new solution effectively reduces the redundant data transferring among gateways, thus greatly enhances the performance of the virtual environment, and that the cost of matching method is relative small in multi-domain virtual environment application.

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A time management optimization framework for large-scale distributed hardware-in-the-loop simulation

Dong

2013

Proceedings of the 1st ACM SIGSIM Conference on Principles of Advanced Discrete Simulation

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Large-scale distributed HIL(Hardware-In-The-Loop) simulation is an important and indispensable method for testing and verifying complex engineering systems. An important necessary condition for realizing HIL simulation is that the speedup ratio of full-speed simulation must be greater than 1, and satisfying this condition becomes more and more difficult with the ceaselessly increasing scale of simulation. Aiming at the problem how to maximizing the speedup ratio, a time management optimization framework for large-scale distributed HIL simulation is proposed in this paper. Different from other works on performance optimization of HIL simulation, in this paper, the problem is focused on simulation speedup ratio and is considered in the range of analysis simulation, which means causal abnormity is intolerable. According to this goal, a new formal description framework of distributed simulation is given based on the automata theory. Then the basic objective and condition of distributed simulation are formally analyzed, which results in the conclusion that the classical Local Causality Constraint for distributed simulation is only a sufficient condition rather than sufficient and necessary condition. Based on this, the optimization problem for simulation speedup ratio is radically analyzed and the overall strategy for this problem is given. Considering different conditions, two different levels of optimization mechanisms respectively for time advance and task partition are given. And finally, the application and experiment result shows the effectiveness of the proposed method.

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Algorithm of simulation time synchronization over large-scale nodes

Cited by 4 publications

References 8 publications

Normalized Storage Model Construction and Query Optimization of Book Multi-Source Heterogeneous Massive Data

Normalized Storage Model Construction and Query Optimization of Book Multi-Source Heterogeneous Massive Data

A Publish/Subscribe based correlative matching method for multi-domain virtual environment

A time management optimization framework for large-scale distributed hardware-in-the-loop simulation

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