Research On Cloud Computing Task Scheduling Based On Improved Krill Swarm Algorithm

Cloud computing task scheduling is one of the important technologies in modern society,and intelligent and efficient task scheduling is crucial for improving computing resource utilization,reducing operational costs,and meeting user needs.With the continuous development of cloud computing task scheduling algorithms,this technology is increasingly widely used in the field of cloud computing.However,currently,cloud computing task scheduling still faces problems such as complex cluster running environments,large number of submitted tasks,and slow task scheduling processing time.In recent years,heuristic algorithm learning has made significant progress in theoretical research.This article aims to learn a cloud computing task scheduling algorithm based on heuristic algorithms to solve the above problems.The main work of this article is as follows:(1)This paper analyzes the current development trend of cloud computing and the research status of task scheduling in cloud computing environment,and analyzes the advantages and disadvantages of intelligent heuristic scheduling and traditional task scheduling algorithm in detail.According to the characteristics of krill swarm algorithm(KH)and the requirements of cloud computing task scheduling,the strategy of cloud computing task scheduling by improved krill swarm algorithm is designed.(2)Based on Cloud Sim simulation tools,the adaptive inertia force weight combined with krill algorithm,the new algorithm comparison test,analysis and summary,compared the time span difference between several algorithm,proposed that this algorithm has certain advantages.(3)A hybrid algorithm(AIPSOKH)based on krill swarm and improved particle swarm was designed to further improve the characteristics of the hybrid algorithm and refer to the population evolution concept improvement algorithm.Choose KH algorithm in the induced weight and foraging weight of discrete system drops countermeasures,and improves with double population countermeasures,and inertial weight index value of particle swarm algorithm(NPSO)mix,finally through the 8 standard test function,reference to each algorithm difference experiment shows that AIPSOKH algorithm in conclusion accuracy and global search level is more advantages.