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Mine mobile crowd sensing task distribution method based on weighted undirected graph

A technology of mobile crowd sensing and weighted undirected graphs, which is applied in the direction of instruments, data processing applications, resources, etc., can solve problems such as not considering the group attributes of terminal carriers, and achieve shortened task allocation time, reasonable task allocation, and improved The effect on success rate

Active Publication Date: 2021-07-23
CHINA UNIV OF MINING & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0012] The purpose of the present invention is to overcome the problem in the prior art that the assignment of tasks does not consider the group attributes of the terminal carriers, and provide a mine mobile crowd sensing based on weighted undirected graphs assigned according to the group attributes of the terminal carriers Task distribution method

Method used

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  • Mine mobile crowd sensing task distribution method based on weighted undirected graph
  • Mine mobile crowd sensing task distribution method based on weighted undirected graph
  • Mine mobile crowd sensing task distribution method based on weighted undirected graph

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0154] A mine mobile group intelligence task distribution method based on a weighted undirected graph. The task distribution method is suitable for mines covered by network signals. Each individual miner carries an intelligent terminal that can connect to the network, and the intelligent terminal can detect miners. heart rate and downhole status;

[0155] The task distribution method includes the following steps:

[0156] Step 1: Establish a miner reputation model,

[0157] Define the participant's reputation as R(u i ), the value range of reputation is [0,1]. A value of 0 indicates that the miner is completely untrustworthy, a value of 0.5 indicates uncertainty, and a value of 1 indicates complete credibility. Participants who participated in the perception task for the first time had an initial reputation of 0.5;

[0158] According to the similarity of task completion location, task completion time similarity and task completion quality, the miner reputation model R(u i ...

Embodiment 2

[0209] Embodiment 2 is basically the same as Embodiment 1, and its difference is:

[0210] Step 3: In the establishment of the task set and the miner status information database, for the task type, gray coding is used to encode the task type Carry out division, carry out conditional constraints on the perception time requirements of the perception task, and draw a task type table according to the requirements of the task type, as shown in the following table:

[0211]

[0212] Underground miners with different functions can complete different types of tasks, and the system selects miners with corresponding functions to complete corresponding types of tasks according to the codes of task types.

Embodiment 3

[0214] Embodiment 3 is basically the same as Embodiment 2, and its difference is:

[0215] Algorithm example:

[0216] Use MATLAB to compare and demonstrate the participant selection mechanism: In order to simulate the real perception task allocation and ensure that the simulation results are close to the facts, the real mine environment is abstracted into a weighted undirected graph with 30 nodes, and N perception tasks, M users are randomly distributed among the edges or nodes of the undirected graph. In addition, set the upper limit of the total number of users M=60, the upper limit of the number of tasks N=50, and the reputation value Ci of each participant and the perceived quality of each user obey the uniform distribution on [0,1] to verify the model of the present invention Effectiveness of strategies and solutions. The specific experimental groups and parameter settings are shown in the table below:

[0217]

[0218]

[0219] The goal of the urgent task alloc...

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Abstract

The invention discloses a mine mobile crowd sensing task distribution method based on a weighted undirected graph, the task distribution method is suitable for a mine covered with network signals, each miner carries an intelligent terminal capable of being connected with a network, and the intelligent terminal can detect the heart rate and the well descending state of the miner; the task distribution method comprises the following steps: step 1, establishing a miner creditworthiness model; step 2, making an undirected path diagram; step 3, establishing a task set and a miner state information base; step 4, distributing emergency tasks; according to the design, the path range is calculated by adopting the weighted undirected graph, the tasks are classified, different types are allocated in different modes, and the task allocation success rate is effectively improved.

Description

technical field [0001] The invention relates to a mine mobile group intelligence sensing task distribution method based on a weighted undirected graph, which is particularly suitable for the intelligent distribution of underground tasks. Background technique [0002] Smart mobile devices (mobile phones, tablets, etc.) can not only be used as mobile devices for daily communication, but also because of their embedded sensors, such as acceleration sensors, digital compass, gyroscope global positioning system (GPS), microphones and cameras, etc. Using these sensors as a sensing unit makes it possible to share sensing data. Mobile crowd sensing is such a new type of perception network that utilizes the sensors of ordinary users' mobile devices for perception. [0003] At present, the research on mobile crowd sensing mainly focuses on the following aspects: (1) research on the application system of crowd sensing in different fields such as co-location and environment detection; (...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/02
CPCG06Q10/06311G06Q10/06313G06Q10/06315G06Q50/02
Inventor 江海峰王梓蒙肖硕张宇
Owner CHINA UNIV OF MINING & TECH
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