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A distribution method for multi-type tasks in spatial crowdsourcing

A technology of task allocation and allocation method, applied in the field of distributed computing, to achieve the effect of increasing the number of tasks completed

Inactive Publication Date: 2017-12-12
HOHAI UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Existing task assignment methods are in a static mode, which contradicts the required timeliness in practical spatial crowdsourcing platforms

Method used

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  • A distribution method for multi-type tasks in spatial crowdsourcing
  • A distribution method for multi-type tasks in spatial crowdsourcing
  • A distribution method for multi-type tasks in spatial crowdsourcing

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Embodiment Construction

[0022] In the following, the present invention will be further clarified with reference to specific examples. It should be understood that these examples are only used to illustrate the present invention and not to limit the scope of the present invention. After reading the present invention, those skilled in the art will understand various equivalent forms of the present invention. All the modifications fall within the scope defined by the appended claims of this application.

[0023] A method for distributing multiple types of tasks in spatial crowdsourcing includes the following steps:

[0024] Step 1: Construct a bipartite graph based on the user task distribution graph, and transform the multi-type task assignment into a maximum weight problem. Such as figure 2 , image 3 As shown, it mainly includes the following two parts:

[0025] (1) Assuming that all users can only accept at most one task, in the time instance s i , The online user set is W i ={w 1 ,w 2 ,...,w n }, the as...

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Abstract

The invention discloses a method for allocating multi-type tasks in space crowdsourcing, combining the characteristics of multiple types of tasks and users in space crowdsourcing, and adopting an allocation algorithm based on the distance ε value to allocate tasks to appropriate users, so as to improve the quality of task completion . The method comprises the following steps: 1) Convert multi-type task allocation into a maximum weight problem, and use the method in the bipartite graph to solve it. 2) Combining with the location attribute of space tasks, the allocation method based on the distance ε value is used to select ε tasks within the closest range to the user and assign them to the user, so as to ensure that the user's mobile cost is within an acceptable range and improve the quality of task completion.

Description

Technical field [0001] The invention relates to a method for distributing multiple types of tasks in space crowdsourcing, and belongs to the field of distributed computing technology. Background technique [0002] Crowd sourcing refers to "a distributed problem solving model in which work tasks performed by full-time employees in the past are outsourced to non-specific solution providers and groups in a voluntary manner through an open Web platform." The early question and answer platform Yahoo! Answers, wikipedia, Baidu knows, etc. are all crowdsourcing platforms. Large crowdsourcing platforms such as AmazonMechanical Turks, CrowdFlower, oDesk, etc. appeared later. With the popularization of smart phones and the improvement of wireless broadband networks, a new development direction of crowdsourcing has been formed-Spatial Crowdsourcing. In crowdsourcing, users only need to perform tasks online and submit the results of the tasks, while in spatial crowdsourcing, users must mo...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06
CPCG06Q10/06311
Inventor 毛莺池王绎超包威戚荣志陈豪平萍
Owner HOHAI UNIV
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