A trust-based task scheduling method for mobile edge users

Abstract

The invention discloses a method for task scheduling of mobile edge users based on trust. By evaluating the trust of mobile edge users, reliable users are selected to perform tasks, and the optimization of task scheduling is realized. The inventive method is divided into two components. 1: Based on a greedy selection algorithm that considers trust, recruit mobile edge users with high trust and low cost to perform tasks, so as to obtain credible evaluation results, accurately identify the reliability of IoT devices in the network, and collect data generated by reliable devices . 2: Comprehensively use the aggregation-based trust reasoning mechanism and the UAV-assisted active trust acquisition mechanism to conduct trust evaluation and reasoning for mobile edge users. Introduce drones to actively verify data uploaded by mobile edge users, thereby improving the accuracy of trust assessment. The trust-based task scheduling optimization method proposed by the present invention can effectively improve the recruitment performance of the cloud and reduce the recruitment cost.

Description

technical field [0001] The invention relates to a trust-based mobile edge user task scheduling method. Background technique [0002] With the rapid development of the Internet of Things and 5G and higher networks, a large number of data-collecting and data-based applications have emerged. The rise of the Internet of Things combined with the current 5G and higher networks has caused major changes in the current network structure. On the one hand, a large number of computing resources are deployed at the edge of the network, so that data processing and analysis can be carried out at the edge of the network, reducing the energy consumption and delay of data upload to the cloud, and bringing better service quality to users. On the other hand, the acquisition of a large amount of data has rapidly increased the types of applications that can be built. Due to the richer frequency, breadth, and granularity of acquired data, the functions and scope of application provided by applica...

AI Technical Summary

Problems solved by technology

[0005] First, for the new open and distributed IoT network, the traditional trust evaluation mechanism is difficult to obtain trust relationship and difficult to accurately evaluate

In the current Internet of Things, a huge number of mobile Internet of Things devices can become mobile data collectors. It is up to each mobile data collector to submit data to the system by itself. The trust evaluation system is limited by observation costs, privacy, etc. Unable to get mobile data collector interaction behavior

In addition, even if the interaction behavior of the mobile data collector is obtained, the trust evaluation system cannot give an effective trust evaluation because it cannot evaluate whether the data submitted by the mobile data collector is authentic or not.

[0006] Second, there are problems of being easily deceived and difficult to verify

The evaluation information used in the traditional trust reasoning and evolution mechanism comes from the evaluation results submitted by the evaluation object itself, and it is difficult to guarantee its accuracy for malicious evaluation objects

Some evaluation systems use a method that comprehensively considers the evaluation results submitted by the two parties in the interaction, which is easily deceived by the joint conspiracy of the two parties in the interaction.

[0007] Third, there is the problem of long timeliness required for evaluation

The traditional trust evolution mechanism needs to observe the interactive behavior of the evaluated object to obtain the evaluation result. The time required for evaluation cannot be controlled by the system. For example, if the evaluated object has no interactive behavior for a period of time, the system will not be able to trust it for a long time degree to evaluate

Images