Storage and indexing method and system based on traffic consumption model event

Abstract

Disclosed are driving amount model event-based storage and index methods and a system. A driving amount model event is set and the amount model event comprises driving amount associated rules corresponding to different projects of different information main bodies. Data for Internet of vehicles comprises raw data and historical data provided by each information main body for the Internet of vehicles, wherein the driving amount model event and a coarse-grained-level index of a sub-space under the driving amount model event are used for the raw data for the Internet of vehicles, and a fine-grained-level index at a record level is set for the historical data in the driving amount model event. Therefore, the methods and the system provided by the present invention reduces a number of index update times and makes the data for the Internet of vehicles distributed evenly when storing and indexing the data for the Internet of vehicles.

Description

technical field [0001] The invention relates to the field of Internet of Vehicles, in particular to a method and system for storing and indexing events based on a vehicle usage model. Background technique [0002] With the continuous maturity of related technologies of the Internet of Vehicles, sensor technology, mobile communication technology, big data technology and intelligent computing technology have all begun to deeply integrate with the Internet of Vehicles industry. Driven by market demand, the Telemaitcs terminal equipment of the Internet of Vehicles is expected to usher in explosive growth. Among them, Telemaitcs refers to the on-board computer system that applies wireless communication technology, thereby bringing considerable value-added income and sustainable development of data service models for operators. opportunity for growth. Different from the traditional intelligent transportation system (ITS, Intelligent Transport System), the Internet of Vehicles pay...

AI Technical Summary

Problems solved by technology

However, how to store and index the raw data of the Internet of Vehicles and optimize resource storage and management is still a problem

This is because, when the above two methods are applied to the storage and indexing of the original data of the Internet of Vehicles, there are the following problems: First, when the data management system based on distributed storage is used to store and index the original data of the Internet of Vehicles, since the system uses The most important is the distributed architecture design, so for the original data query of the Internet of Vehicles with a relatively low selection rate, the performance is relatively poor; secondly, the R-Tree method used in the cloud storage-based two-layer index method is used as a local index and a global index. In the indexing process of the original data of the Internet of Vehicles, it is necessary to continuously split and adjust the computer nodes. The maintenance cost of the index is too high, which has a great impact on the throughput of the Internet of Vehicles system.

Most importantly, the above two methods do not fully consider the relationship between the original data and information subjects of the "people-vehicle-road" network of vehicles, lack of pertinence, and cannot provide convenience for subsequent analysis and processing based on traffic incidents

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