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A Robust Mobile Crowd Sensing Algorithm Based on Edge Computing

A mobile crowd-sensing and edge computing technology, applied in location-based services, computing, instruments, etc., to solve problems such as bandwidth resource consumption and high latency

Active Publication Date: 2021-12-31
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At the same time, the traditional MCS system relies on a central server to process all sensory data, which will result in the consumption of a large amount of bandwidth resources and high latency

Method used

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  • A Robust Mobile Crowd Sensing Algorithm Based on Edge Computing
  • A Robust Mobile Crowd Sensing Algorithm Based on Edge Computing
  • A Robust Mobile Crowd Sensing Algorithm Based on Edge Computing

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Embodiment Construction

[0063] The embodiment of the present invention is divided into two steps, the first step is to build a model, and the second step is to implement the algorithm. Among them, the model established as figure 1 As shown, it completely corresponds to the introduction of robust mobile crowd perception based on edge computing in the summary of the invention; and the implementation process of the algorithm is determined by image 3 and Figure 4 give. image 3 is a structural diagram of the proposed invention, reflecting the flow of data. The present invention conducts extensive simulations to evaluate the performance of the proposed RMCS framework. Among them, this section conducts a case study of PM2.5 concentration prediction, Figure 4 It is a data prediction task for error detection and error correction based on deep learning, which completely corresponds to the algorithm steps in which only one type of sensing task is considered in the summary of the invention.

[0064] 1) ...

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Abstract

The invention relates to an optimization algorithm based on edge computing that is applied in the MCS (Mobile Crowd Sensing) sensing task scene, and is based on the recruitment of task participants, the judgment of information validity, and the detection and correction of errors. The present invention represents platform utility as a logarithmic function (strictly increasing and sagging) of independent measurement data for each location, and the algorithm aims to maximize total utility under exerting budget constraints. Since the proposed joint optimization problem is a non-deterministic polynomial combinatorial optimization problem, it cannot be solved in polynomial time. Therefore, we design an approximation algorithm that greatly reduces the computational complexity. The present invention uses a deep neural network (DNN) for data verification, thereby increasing the accuracy of predicted data. In addition, the present invention also adopts data redundancy to improve the sensing quality, and when measurement errors are detected near the data source, the amount of data transmitted from the base station to the sensing platform is greatly reduced, the occupied frequency band resource is reduced, and the time delay is reduced.

Description

technical field [0001] The present invention belongs to the field of wireless communication, and specifically relates to an optimization based on edge computing for the recruitment of task participants, the judgment of information validity, and the detection and correction of errors applied in the MCS (Mobile Crowd Sensing) sensing task scene Algorithms can ensure that more users are recruited to participate in sensing tasks under a limited budget to obtain greater sensing coverage; they can process uploaded data on the basis of ensuring the quality of service of user equipment to obtain higher quality The data can effectively solve the problems of big data, big capital and large coverage such as environmental monitoring and data forecasting. Background technique: [0002] To establish a safe and stable society, it is necessary to establish effective monitoring of various social information such as traffic conditions, air quality, and natural disasters. The rapid developmen...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04W84/18G06Q50/00G06Q30/06G06Q30/08G01D21/02
CPCH04W84/18H04W4/02G06Q30/08G06Q30/0611G06Q50/01G01D21/02H04L67/51
Inventor 廖海君周振宇
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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