CAJ | 학술논문

云计算环境下的任务调度方法是实现其高效计算的关键步骤,文章针对目前其时间效率低下的问题提出了一种基于改进的粒子群算法的任务调度方法,利用迭代选择算子引入粒子群来完成任务调度的优化。改进的粒子群算法（Improved particle swarm optimization,IPSO）,提高了算法的优化能力,尽量避免陷入局部最优,收敛的效果更好从而减少任务调度时间开销。选择CloudSim仿真平台进行模拟,实验结果表明,该改进算法具有寻优能力强、时间耗时少的优点,可用于云计算问题中复杂调度优化的研究与应用。
운계산배경하적임무조도방법시실현기고효계산적관건보취,문장침대목전기시간효솔저하적문제제출료일충기우개진적입자군산법적임무조도방법,이용질대선택산자인입입자군래완성임무조도적우화。개진적입자군산법（Improved particle swarm optimization,IPSO）,제고료산법적우화능력,진량피면함입국부최우,수렴적효과경호종이감소임무조도시간개소。선택CloudSim방진평태진행모의,실험결과표명,해개진산법구유심우능력강、시간모시소적우점,가용우운계산문제중복잡조도우화적연구여응용。
Task scheduling method for cloud computing system is the key steps to achieve its high performance computing,the paper focuses on the low efficiency to propose a new task scheduling method based on improved Particle Swarm Optimization（PSO） algorithm,using the iterative selection operators to add into the particle swarm to finish task scheduling optimization.Improved Particle Swarm Optimization（IPSO）,improves algorithm for the capacity of optimization,as far as possible avoiding a local optimization,better effect of convergence task scheduling which time costs.The CloudSim simulation platform is selected for simulation,experimental results show that the algorithm has the advantage of optimization abilities,and takes less time,It can apply to the task schedule optimization for cloud computing problems in the research.