Open AccessCloud Computing Resource Scheduling Based on Improved Particle Swarm Optimization Algorithm
Author(s) -
Shuai Sun
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2023/1/012025
Subject(s) - computer science , cloud computing , particle swarm optimization , distributed computing , scheduling (production processes) , quality of service , job shop scheduling , architecture , shared resource , mathematical optimization , algorithm , computer network , schedule , operating system , art , mathematics , visual arts
With the limited resources of Cloud computing (hereinafter referred to as CC), we must improve the quality of scheduling and cost optimization. Therefore, we must organically integrate the resource pool of servers and computers, which will distribute resources dynamically according to the needs of users. Through CC Resource scheduling (hereinafter referred to as RS), we can improve resource utilization, which will greatly reduce the use cost. Through the CC sharing architecture model, we can implement QoS according to different needs of users, which can achieve flexible resource allocation. Therefore, we need to reasonably design the CC RS and allocation model, which will improve the resource utilization. At the same time, this algorithm can share information among individuals. However, the general PSO (hereinafter referred to as PSO) algorithm has the problem of discretization. This paper proposes an Improved PSO (hereinafter referred to as FPSO) algorithm, which can better solve the RS problem. Firstly, the goal of task scheduling is proposed. Then, an FPSO algorithm is proposed. Finally, some suggestions are put forward.