Application Research On Hybrid Particle Swarm Algorithm For Cloud Computing Task Scheduling

Cloud computing is the evolution and development of traditional computing and network technologies,such as distributed computing,parallel computing,cluster computing and grid computing.Task scheduling is one of the core contents of cloud computing,it's also one of the hot topics in the word.In the light of various requirements of tasks submitted by users,using the proper methods to allocate different tasks to the appropriate computing nodes in the cloud environment,which has a direct impact on the total task execution time,the total cost of resource consumption and the overall load balance and other important factors.Therefore,it is of great theoretical and practical significance to explore and discuss the application of more efficient intelligent optimization algorithms in task scheduling problem.In this paper,a hybrid particle swarm optimization(HPSO)algorithm based on cloud normal model is proposed.HPSO is adopted to solve a cloud task scheduling problem,which is studied and explored in detail.Firstly,this paper studies the application status and development trend of task scheduling algorithms in task scheduling problems.This paper aims at the problem of task scheduling and the rules of the scheduling algorithms,the task scheduling problem is analyzed and modeled,a heuristic HPSO intelligent algorithm is proposed.On the one hand,the Min-Min algorithm is used to initialize the population randomly,which solves the problem of low initial solution quality and improves the quality of the particles;On the other hand,this paper uses the normal cloud model to dynamically change the particle inertia weight,at the same time combines genetic algorithm,adaptive crossover and mutation operation are proposed to preserve excellent particles,which effectively solves the problem of falling into the local minimum easily.It not only enhances the ability of local and global search,but also increases the search speed and improves the diversity of the population.Secondly,the proposed task scheduling scheme is simulated and analyzed in Cloud Sim simulator,this paper evaluates the performance of HPSO algorithm in task scheduling,by the compared results of three performance objectives,which verifies the feasibility and robustness of the algorithm.Finally,through the simulation of task scheduling process in a certain enterprise,this paper designs and implements a task scheduling management system based on HPSO algorithm,which is realized rapid and efficient allocation of tasks,further validating the usefulness and accuracy of this algorithm.