High-dimension space-time field data real-time transmission method under limited network bandwidth constraint

Abstract

The invention discloses a high-dimension space-time field data real-time transmission method under limited network bandwidth constraint. According to the method, data is organized through utilizationof a tensor structure; through comprehensive assessment on to-be-transmitted data and a transmission network environment, a reasonable tensor hierarchical policy and a tensor compression parameter areselected; a new hierarchical tensor compression structure is defined; and on the basis of the compression structure, a data compression and streaming transmission method adaptive to the network environment is established. Tensor dynamic addition and on-demand reconstruction mechanisms are designed at a data receiving client, so the occupation for a client memory and system resources is greatly reduced. Through utilization of case data, the process is verified. A result shows that the method is characterized by real-time transmission and high precision. A high-dimension and massive data real-time transmission demand under the limited network bandwidth environment is satisfied.

Description

technical field [0001] The invention relates to a transmission method of high-dimensional field data, in particular to a real-time transmission method of high-dimensional space-time field data under the constraint of limited network bandwidth. Background technique [0002] With the improvement of the earth observation system and the attention to the study of large-scale dynamic phenomena, high-dimensional and massive spatio-temporal field data involving multiple fields and different attributes, such as remote sensing and meteorological data, have grown rapidly. The above-mentioned geo-current data has the characteristics of large data volume, high dimensionality, and fast update time. It has the following major difficulties in the process of processing: ① geo-current data is often very large, and even a slice of data can reach several GB; ② data The dimension is very high, and it is inseparable because it needs to participate in the calculation at the same time; ③The analysi...

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Problems solved by technology

[0005] The paper titled "A Hierarchical Tensor-Based Approach to Compressing, Updating and Querying Geospatial Data" discloses a calculation method of hierarchical tensors, which compresses dynamic data window by window through the data window. The value of Rank is single when the accuracy is high, and it is impossible to dynamically adjust data compression under the constraint of limited bandwidth according to the actual network transmission status and transmission conditions, resulting in unreasonable occupancy of client memory and system resource space

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