CAJ | 학술논문

如何对任务进行高效合理的调度是云计算需要解决的关键问题之一，针对云计算的编程模型框架，在传统粒子群优化算法（PSO）的基础上，提出了一种具有双适应度的粒子群算法（DFPSO）。通过该算法不但能找到任务总完成时间较短的调度结果，而且此调度结果的任务平均完成时间也较短。仿真分析结果表明，在相同的条件设置下，该算法优于传统的粒子群优化算法，当任务数量增多时，其综合调度性能优点明显。
여하대임무진행고효합리적조도시운계산수요해결적관건문제지일，침대운계산적편정모형광가，재전통입자군우화산법（PSO）적기출상，제출료일충구유쌍괄응도적입자군산법（DFPSO）。통과해산법불단능조도임무총완성시간교단적조도결과，이차차조도결과적임무평균완성시간야교단。방진분석결과표명，재상동적조건설치하，해산법우우전통적입자군우화산법，당임무수량증다시，기종합조도성능우점명현。
How to schedule tasks efficiently is one of the key issues to be resolved in cloud computing environment. A Double Fitness Particle Swarm Optimization algorithm(DFPSO)based on conventional Particle Swarm Optimization(PSO)is brought up for the programming framework of cloud computing. Through this algorithm, the better task scheduling not only shortens total task completion time and also has shorter average task completion time. Simulation results show that DFPSO is better than PSO, and the integrated scheduling performance is excellent, especially when the number of tasks increases.