Crowdsourcing service-oriented task allocation method and system for Internet of Vehicles

Abstract

The invention discloses a crowdsourcing service-oriented task allocation method and system for the Internet of Vehicles, and the method comprises the steps: obtaining a task estimation value accordingto task data returned by each vehicle in a task range; dividing quality grades according to the deviation between the task data returned by each vehicle and the task estimation value; setting a coverage range of the vehicles, and calculating a set of other vehicles covered by each vehicle based on the coverage range; selecting a task execution vehicle set with an approximately optimal data quality grade based on a set coverage method, wherein all task vehicles in the task execution vehicle set can realize full coverage of each vehicle in a task range; and sending the crowdsourcing task to allthe task vehicles. According to the invention, the data quality of the vehicle can be estimated in real time, and task allocation is performed on the request of the user according to the data qualitygrade and the vehicle relative position; and the data quality grade of the selected task vehicle is high, so that the purposes of reducing crowdsourcing answer redundancy and reducing system transmission overhead can be achieved.

Description

technical field [0001] The present invention relates to the technical field of the Internet of Vehicles, in particular to a task allocation method and system for crowdsourcing services of the Internet of Vehicles. Background technique [0002] Crowdsourcing is a distributed problem-solving mechanism that is open to the public on the Internet. It solves problems that are difficult for machines to complete alone by integrating computers and the unknown public on the Internet. [0003] Vehicles carry out crowdsourcing service collaboration through the Internet of Vehicles, which utilizes mobile devices with multi-functional sensors. Compared with other mobile devices, they have rich on-board resources and stronger processing, storage and sensing capabilities. It can also easily collect data on a large scale, such as collecting road traffic congestion, urban WiFi access points, or measuring environmental phenomena such as air quality and noise pollution levels. [0004] Crowdso...

AI Technical Summary

Problems solved by technology

[0005] When the Internet of Vehicles crowdsourcing system allocates tasks, it needs to consider the data quality and vehicle location, and reduce the transmission overhead while ensuring the crowdsourcing answers. However, the current Internet of Vehicles crowdsourcing system still has the following defects: (1) The quality of crowdsourcing answers Relatively low has always been the bottleneck problem in the crowdsourcing platform. Since participating in crowdsourcing tasks will get rewards, some participants in crowdsourcing tasks may commit fraud in order to defraud the rewards, which makes it difficult to guarantee the quality of crowdsourcing answers submitted

(2) The vehicle network crowdsourcing service needs to consider the location of the vehicle. The sensing data collected by vehicles with similar locations are often close in value. Therefore, assigning tasks to vehicles with similar locations will lead to data redundancy, and the redundant data will be returned to the edge server. It will inevitably increase the transmission overhead and communication cost

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