Data organization method oriented to sea-cloud collaboration network computing network

Abstract

The invention relates to a data organization method oriented to a sea-cloud collaboration network computing environment and called DataCap. Primary components of the DataCap are data bodies and data algebraic numbers, the data bodies provide containers of data content and metadata description information, and the data algebraic numbers are a set of operators of the data bodies. A data body and one or multiple data algebraic numbers matched with the data body jointly form a data layer which corresponds to a link in a specific software service process. According to an upstream-downstream dependence relationship of the service process, a data layer chain is formed among the data layers, and corresponding data are constantly processed, fused and converted in the service process. The core components are appointed and described through two auxiliary modules including data unit unified identity and data organization description language. By the data organization method, flexible configuration of computing resources in an information system can be realized; the data organization method meets targes of elastic computing architecture and global resource optimization under a sea-cloud collaboration network.

Description

technical field [0001] The present invention relates to the fields of the Internet of Things, cloud computing, and big data management, and is aimed at the construction requirements of a "human-machine-thing" ternary fusion information society in the strategic pilot plan of the new generation of information technology research "perceiving China", and proposes a A data organization method adapted to the sea-cloud collaborative network computing environment—DataCap (data capsule). Background technique [0002] With the extension of the Internet to the physical world, the information technology represented by the Internet of Things has accelerated the process of world informatization and rapidly expanded the information network of human society to the physical world. Hundreds of millions or billions of sensing devices are constantly sensing the dynamically changing physical world, and are connected and integrated with each other. Through various mobile communication devices, co...

AI Technical Summary

Problems solved by technology

Specifically, the existing cloud computing and big data technologies follow the "big centralized datacenter" + XaaS, which belongs to the data intensive architecture, and it is difficult to directly match Haiduan and Haiyun in the collaborative network computing environment of Haiyun. Collaborative features, unable to utilize the local computing power at the sea end and the collaborative task distribution capability of the network, resulting in unnecessary waste of infrastructure resources in the information society

[0007] 2) The data organization methods in the existing cloud computing and big data technologies are not suitable for the Haiyun collaborative network environment

Works similar to the present invention include: 1) The "cloud + terminal" strategic planning of Microsoft Research (MSR) is somewhat similar to some concepts of Haiyun Collaborative Network, but Microsoft mainly focuses on integrating and packaging existing products and technologies for business 2) The "Data DNA" report released by the Brookings Institution (Brookings) in 2005, they only focus on the standardization of statistical data Metadata description specification, regardless of data processing and distribution process and computing mode; 3) Tachyon system developed by AMPLab of the University of California, Berkeley (UCB), in which through elastic distributed data set (RDD) and its association (Lineage) to represent the data processing process and related repair methods, mainly applicable to cloud computing platforms such as Hadoop and Spark, without considering collaborative computing scenarios including thin terminals (sea terminals)

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