CAJ | 학술논문

针对云计算环境下的资源调度优化问题，提出了一种基于量子粒子群策略的混洗蛙跳改进算法（简称QPSFLA算法），旨在引入量子粒子群搜索策略防止传统混洗蛙跳算法容易陷入局部最优的问题。在CloudSim平台上的模拟试验结果表明，QPSFLA算法能够达到预期效果，而且比平台自带算法和传统混洗蛙跳算法效率更高。
침대운계산배경하적자원조도우화문제，제출료일충기우양자입자군책략적혼세와도개진산법（간칭QPSFLA산법），지재인입양자입자군수색책략방지전통혼세와도산법용역함입국부최우적문제。재CloudSim평태상적모의시험결과표명，QPSFLA산법능구체도예기효과，이차비평태자대산법화전통혼세와도산법효솔경고。
For the optimization problem of the cloud competing resource scheduling, this paper proposed a strategy based on quantum particle swarm shuffled frog leaping algorithm. This algorithm using quantum particle swarm search strategy in the local search to avoid falling into local optimum. By cloudsim platform simulation tests show that the algorithm has validity, and im-proved shuffled frog leaping algorithm more efficient than the original algorithm.