Research On Improved Particle Swarm Algorithm And Applied In Cloud Computing Resource Scheduling

In our daily life, many problems encountered are actually problem of optimation. It can help us choose a best solution from many schemes. In order to solve the optimization problem, we need to find a more efficient algorithm. As a kind of swarm intelligence algorithm, particle swarm algorithm causes the attention of the experts and scholars from the birth. After a long time of development, particle swarm algorithm has been widely used in every field. It also is a kind of efficient algorithms to solve the problem of optimization.The main works of the dissertation can be summarized as follows:(1) This Paper makes a brief introduction of the basic theories and algorithm implementation of standard particle swarm algorithm. In the paper, the parameters of particle swarm optimization are researched and the corresponding emulator experiments are carried out.(2) There is early maturing and easily falling into a local optimum of the problem about the traditional particle swarm algorithm, the paper will be integrated into the local version of the idea to the standard particle swarm optimization algorithm, through the global optimal solution and the optimal solution in the field at the same time acting on the particle flight, speed update formula was improved, and it made the particle at the same time to the global optimal solution and the optimal solution in the field of learning.(3) Based on previous theoretical studies, it has improvements about the equations of motion in the inertia weight and learning factors and constraints and other factors, this paper presents an approach algorithm based on changing inertia weight of learning and constraint factors. By setting several groups of experiments and making comparison with two other algorithms in the references,we illustrate the feasibility and validity of this new algorithm.(4) In order to demonstrate the algorithm’s performance in practical application, we put the algorithm to the problem of resource scheduling in cloud computing. This algorithm was run under the cloud computing simulation platform-Cloudsim. In this paper, compared time scheduling and dispatching cost with new particle swarm optimization, standard particle swarm optimization and RR algorithm in Cloudsim,we found that the algorithm performance in the resource scheduling problem is superior to the standard particle swarm optimization algorithm and RR algorithm.