基于改进萤火虫算法的云计算任务调度算法

Cloud computing task scheduling algorithm based on improved firefly algorithm

针对云计算环境中的大量任务,为提高资源利用率,缩短任务完成时间,提出了一种基于改进萤火虫算法的任务调度算法。首先用每只萤火虫的位置表示一种可行的调度方案,利用自然数对萤火虫进行编码表示其所在位置,并随机初始化种群;然后在搜索过程中利用混沌扰动对适应度函数值较低的萤火虫进行激活,保持种群活性,利用真实物理反弹理论对飞出搜索区域的萤火虫进行控制,维护种群多样性,降低陷入局部最优的概率。在CloudSim平台进行仿真测试,结果表明,该算法能够有效缩短任务完成时间,且寻优结果更佳。

In order to improve the utilization rate of resources and shorten the task completion time,a task scheduling algorithm based on improved firefly algorithm was proposed to deal with a large number of tasks in the cloud computing environment.Firstly,the location of each firefly was used to express a feasible scheduling scheme,and natural numbers were applied to encode fireflies and represent their locations.Meanwhile,the population was randomly initialized.Secondly,in the search process,chaos disturbance was used to activate the firefly with low fitness function value and maintain the population activity.Real physical rebound theory was utilized to control the firefly flying out of the search area so as to maintain the population diversity and reduce the probability of falling into local optimal.Finally,the simulation test of CloudSim platform was conducted.The test results show that the algorithm can shorten the task completion time and the optimization result is better.