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Two-way auction-based method of mobile group intelligence perception and resource allocation and incentive mechanism thereof

A mobile crowd-sensing and resource allocation technology, applied in the field of mobile crowd-sensing based on two-way auction and its resource allocation and incentive mechanism, can solve the problems of incompetence, low-end configuration and performance, etc.

Inactive Publication Date: 2018-09-28
SOUTHEAST UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although the current smart devices are updated quickly, in the transmission of high-speed data and some perception tasks with higher quality requirements, general smart devices still face the relatively low-end configuration and performance, which makes them unable to perform certain high-end tasks. The problem of the required task. At this time, the smart device with poor performance needs to seek high-performance resource supply to improve its performance, so as to better participate in the mobile crowd sensing task that it wants to participate in. The high-performance resource supply party It can be other active high-reputation smart devices, or it can be a micro-cloud in mobile swarm intelligence computing

Method used

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  • Two-way auction-based method of mobile group intelligence perception and resource allocation and incentive mechanism thereof
  • Two-way auction-based method of mobile group intelligence perception and resource allocation and incentive mechanism thereof
  • Two-way auction-based method of mobile group intelligence perception and resource allocation and incentive mechanism thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0081] Example 1: In order to verify the computational effectiveness of the DAIM algorithm, according to the number of people set in Table 1, each group randomly generated 100 instances, and averaged the computing time of these 100 instances to ensure the reliability of the results sex. The test experiment of computing effectiveness is carried out on Windows10 system, the processor is Core TM i7-6650UCPU@2.20GHz2.21GHz, RAM is 16.0GB. The experimental settings and results are shown in the table below.

[0082]

[0083] The steps of the experiment are as follows: firstly, the number of buyers n is fixed at 50, the number of sellers m is changed from 50 to 400, and the number of sellers is increased by 50, and the DAIM algorithm is run, in which each group of records randomly generates 100 experiments, and records the 100 times. The average running time of the first experiment; after that, fix the number of sellers m to 50, change the number of buyers n from 50 to 400, and ...

Embodiment 2

[0084] Example 2: In order to verify the individual rationality of the DAIM algorithm, run the DAIM algorithm under the same hardware configuration environment as the above-mentioned calculation effectiveness, the specific settings are 100 sellers and 25 buyers, and analyze the successful pairing between buyers and sellers The relationship between the seller's asking price, the buyer's settlement price and the buyer's quotation. From attached figure 1 It can be seen from the figure that for each buyer in DAIM, the settlement price with the auctioneer will not be higher than his bid price, and each winning seller will get paid no less than his asking price from the auctioneer. price. Therefore, the DAIM algorithm satisfies individual rationality. The results of individual rationality show that when the resources of the smart device itself are not rich enough, when it is necessary to request higher computing performance or higher completion quality from the resource supply par...

Embodiment 3

[0086] Example 3: In order to verify the authenticity of the DAIM algorithm, randomly select buyers and sellers among randomly generated buyers and sellers, and observe the changes in buyer / seller utility caused by changes in the buyer's quotation / seller's asking price, as shown in the attached Figure 2 to Figure 5 As shown, both the buyer and the seller meet the nature of authenticity. Divide the experiment into 4 sub-experiments, and conduct experimental research and analysis on the utility changes of winning buyers, non-winning buyers, winning sellers, and non-winning sellers respectively. The settings and configuration of the experiment are the same as the above-mentioned individual rational experiment, and the authenticity research of the DAIM algorithm is conducted for 100 sellers and 25 buyers.

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Abstract

The invention discloses a two-way auction-based method of mobile group intelligence perception and resource allocation and an incentive mechanism thereof. The method is suitable for use in mobile group intelligence perception. Certain users are limited by perception resources and data collection conditions of equipment which is thereof and cannot provide high-rate high-quality data resources withdiversity, and need the aid of resources of other equipment to participate in scenes of mobile group intelligence perception. Under the scenes, on the one hand, the intelligent equipment can provide the richer resources by the aid of powerful computing capability of a micro cloud, and on the other hand, a data exchange network among the equipment can be established by the aid of other intelligentequipment with good performance status and high credibility. A process thereof involves two-way auction between the intelligent equipment and the micro cloud or between the intelligent equipment, andtherefor, auction theory can be applied to study resource allocation and incentive-mechanism design thereof.

Description

technical field [0001] The invention relates to the technical field of two-way resource allocation and incentive algorithm among intelligent devices in mobile crowd sensing, in particular to mobile crowd sensing based on two-way auction and its resource allocation and incentive mechanism method. Background technique [0002] In mobile crowd sensing, the main participants are smart devices carried by users. Although the current smart devices are updated quickly, in the transmission of high-speed data and some perception tasks with higher quality requirements, general smart devices still face the relatively low-end configuration and performance, which makes them unable to perform certain high-end tasks. The problem of the required task. At this time, the smart device with poor performance needs to seek high-performance resource supply to improve its performance, so as to better participate in the mobile crowd sensing task that it wants to participate in. The high-performance r...

Claims

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Application Information

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IPC IPC(8): G06Q30/08
CPCG06Q30/08
Inventor 杨绿溪杨堤李卓青徐琴珍李春国黄永明
Owner SOUTHEAST UNIV
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