Research On Task Collaboration Of Computing Nodes Based On Trust Computing

Compared with the cloud computing model of centralized data processing,edge computing has ad hoc network capabilities and task self-coordination capabilities,and its task collaborative processing mechanism has important research value.However,the complexity and dynamics of the edge computing environment itself also cause system security and performance issues to become more prominent.In order to make the edge network provide better services,how to implement a secure and trusted computing resource sharing environment to make efficient and reasonable task migration decisions has received more and more attention from researchers.This paper focuses on the requirements for credibility and efficiency in the collaborative environment of edge computing tasks.First of all,in order to meet the growing demand for reliability of nodes in an open edge computing collaborative environment,this paper studies a multi-dimensional trust evaluation model for edge computing nodes.This method comprehensively calculates the trust value of the node based on multiple dimensions,which improves the performance of the node in the face of malicious attacks and avoids the joining of nodes that restrict the task completion.Based on this,a dual filtering algorithm based on K-Means clustering is proposed to effectively filter low task similarity and feedback from malicious devices.In addition,the low complexity of the overall algorithm design ensures that the trust mechanism is lightweight and suitable for large-scale edge computing environments.Finally,we analyzed the results of trust calculation based on simulations,and proved that our trust computer system is superior to other comparison algorithms in reliability and robustness.Secondly,in order to solve the problem of efficient task migration in a multi-user multi-tasking collaborative scenario,this paper further proposes a trusted computing task migration algorithm for edge computing.The algorithm fully considers the dependencies within the task,models the fine-grained migration scenario of the task,and studies the calculation model and queuing model in the task migration environment.The task migration scheme for optimizing the corresponding time of the overall task is researched,and a hybrid genetic algorithm that combines the characteristics of trust and greed is designed to improve the efficiency of task migration and ensure the trust needs in a collaborative task environment.Finally,the effectiveness of the algorithm is verified by simulation experiments.In a word,this paper studies the problem of node trust and task migration in the collaborative computing environment of edge computing,which aims to improve the overall credibility and time of the system and solve the trusted task coordination problem faced by edge computing.