The Design of Data Security Synchronization in the Network of Satellite and Ground Security Management Instrument

2010 ◽  
Vol 439-440 ◽  
pp. 208-214 ◽  
Author(s):  
Qian Mu Li ◽  
Rui Wang ◽  
Jie Yin ◽  
Jun Hou
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Network Performance ◽  
High Efficiency ◽  
Security Management ◽  
Direct Access ◽  
Data Synchronization ◽  
Buffer Size ◽  
Synchronization Mechanism ◽  
Management Instrument

Network security, data management, data synchronization Abstract. The aim of Network of Satellite and Ground Security Management Instrument (NSGMI) is to increase network availability, improve network performance and control operation costs. After analyzing the shortcomings of traditional data synchronization mechanism, this paper reconstructs data processing method to improve communication ability of NSGMI, and provides a solution to guarantee real time and reliable on the application layer. The new mechanism provides buffer areas and operation flows to satisfy the high efficiency of data processing demand and the strong real time request. It solves how to open the buffer size when a direct access changes records.

Application and Research of Data Interface Synchronization on Web Maintenance

2014 ◽  
Vol 1049-1050 ◽  
pp. 1803-1807
Author(s):  
Xiao Yang Liu ◽  
Jian Ping Zhao ◽  
Qing Mei Li ◽  
Wei Wang ◽  
Ran Ding ◽  
...  
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Incremental Maintenance ◽  
Synchronization Mechanism ◽  
Materialized View ◽  
Maintenance System ◽  
Transfer Orbit ◽  
Database Technology ◽  
Orbit Segment ◽  
The Web

To adapt to the changing requirement of task data interface under the situation of far distance, multiple segment, multiple circle, multiple satellite and multi-station visibility for satellite misson in transfer orbit segment, the web incremental maintenance system based on materialized view was achieved through applying incremental maintenance principle, database technology, synchronization mechanism and maintenance proxy, and realizing the synchronization and consistency of data interface about the distributed experiment information surveillance software system. The result shows that web incremental maintenance system can ensure the real-time and consistency of data processing and transmission.

scholarly journals Real-Time Massive Vector Field Data Processing in Edge Computing

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2602 ◽  
Author(s):  
Kun Zheng ◽  
Kang Zheng ◽  
Falin Fang ◽  
Hong Yao ◽  
Yunlei Yi ◽  
...  
Keyword(s):  
Vector Field ◽  
Data Processing ◽  
Real Time ◽  
Field Data ◽  
High Efficiency ◽  
High Volume ◽  
Edge Computing ◽  
Distributed Sensors ◽  
Massive Vector ◽  
Data Source

The spread of the sensors and industrial systems has fostered widespread real-time data processing applications. Massive vector field data (MVFD) are generated by vast distributed sensors and are characterized by high distribution, high velocity, and high volume. As a result, computing such kind of data on centralized cloud faces unprecedented challenges, especially on the processing delay due to the distance between the data source and the cloud. Taking advantages of data source proximity and vast distribution, edge computing is ideal for timely computing on MVFD. Therefore, we are motivated to propose an edge computing based MVFD processing framework. In particular, we notice that the high volume feature of MVFD results in high data transmission delay. To solve this problem, we invent Data Fluidization Schedule (DFS) in our framework to reduce the data block volume and the latency on Input/Output (I/O). We evaluated the efficiency of our framework in a practical application on massive wind field data processing for cyclone recognition. The high efficiency our framework was verified by the fact that it significantly outperformed classical big data processing frameworks Spark and MapReduce.

scholarly journals MUSiiC ToolKit 2.0: Bidirectional Real-time Software Framework for Advanced Interventional Ultrasound Research

2012 ◽  
Author(s):  
Hyun-jae Kang ◽  
Alexis Cheng ◽  
Emad Boctor
Keyword(s):  
Medical Imaging ◽  
Data Processing ◽  
Real Time ◽  
Data Communication ◽  
Ease Of Use ◽  
Data Synchronization ◽  
Software Framework ◽  
Multiple Sources ◽  
Bidirectional Communication ◽  
Executable Programs

Ultrasound (US) imaging is a popular and convenient medical imaging modality thanks to its mobility, non-ionizing radiation, ease-of-use, and real-time acquisition. Conventional US imaging is frequently integrated with tracking systems and robotic systems in Image Guided Therapy (IGT) systems. Recently, these systems are also incorporating advanced US imaging such as US elasticity imaging, photoacoustic imaging, and thermal imaging. Real-time synchronous data from multiple sources and bidirectional data communication are essential for integrating components in advanced US IGT research. We previously proposed the MUSiiC ToolKit [1], a modular real-time software toolkit, and OpenIGTLinkMUSiiC [2], a standard communication protocol extended from the OpenIGTLink library [3, 4]. However, this software framework only supported real-time synchronous data from at most two sources and unidirectional communication at the software module level and class level.In this paper, we propose MUSiiC ToolKit 2.0, an upgraded software framework for interventional advanced US research sup-porting bidirectional communication, real-time US data processing, and real-time data synchronization from multiple sources. MUSiiC ToolKit 2.0 consists of OpenIGTLink 2.0, OpenIGTlinkMUSiiC 2.0, MUSiiCNotes 2.0, and a collection of executable programs designed for US research. OpenIGTLink 2.0 is a standard TCP/IP-based protocol for the integration of medical imaging and IGT systems. OpenIGTLinkMUSiiC 2.0 is the upgraded version of OpenIGTLinkMUSiiC with new active multi-task classes, data interfaces for supporting bidirectional communication and parallel data processing. MUSiiCNotes 2.0 provides US research-oriented task classes, such as US data acquisition, beamforming, envelope detection, scan conversion, and data synchronization. Graphic User Interface (GUI) units are also available for the executable programs in MUSiiCNotes 2.0. Finally, we introduce advanced US applications based on this new software framework.

scholarly journals The real-time big data processing method based on LSTM or GRU for the smart job shop production process

2020 ◽  
Vol 14 ◽  
pp. 174830262096239 ◽  
Author(s):  
Chuang Wang ◽  
Wenbo Du ◽  
Zhixiang Zhu ◽  
Zhifeng Yue
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Production Process ◽  
Real Time ◽  
Job Shop ◽  
Production Data ◽  
Time Data ◽  
Big Data Processing ◽  
The Real ◽  
Data Processing Method

With the wide application of intelligent sensors and internet of things (IoT) in the smart job shop, a large number of real-time production data is collected. Accurate analysis of the collected data can help producers to make effective decisions. Compared with the traditional data processing methods, artificial intelligence, as the main big data analysis method, is more and more applied to the manufacturing industry. However, the ability of different AI models to process real-time data of smart job shop production is also different. Based on this, a real-time big data processing method for the job shop production process based on Long Short-Term Memory (LSTM) and Gate Recurrent Unit (GRU) is proposed. This method uses the historical production data extracted by the IoT job shop as the original data set, and after data preprocessing, uses the LSTM and GRU model to train and predict the real-time data of the job shop. Through the description and implementation of the model, it is compared with KNN, DT and traditional neural network model. The results show that in the real-time big data processing of production process, the performance of the LSTM and GRU models is superior to the traditional neural network, K nearest neighbor (KNN), decision tree (DT). When the performance is similar to LSTM, the training time of GRU is much lower than LSTM model.

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