混沌扰动w_BAPSO算法在任务调度中的应用

Application of Chaotic Disturbance w_BAPSO Algorithm in Task Scheduling

为提高云计算任务调度效率,减少任务调度的成本和时间,改进算法容易陷入局部最优的缺陷,提出基于混沌扰动的w_BAPSO算法。在云计算环境下,通过引入带有logistics混沌扰动的线性递减惯性权重,在PSO算法更新过程中结合蝙蝠算法脉冲速率、脉冲响度等参数,将带有混沌扰动的w_BAPSO算法用于云计算任务调度过程中。通过Cloudsim云计算仿真软件进行实验验证,分别测试不同任务规模下w_BAPSO算法效能。实验结果表明,基于混沌扰动的w_BAPSO算法不仅能够提高算法的收敛速度和搜索精度,而且减少了云计算任务调度的成本和时间,还提高了任务调度效率。

In order to improve the efficiency of cloud computing task scheduling,reduce the cost and time of task scheduling,and overcome the shortcomings of algorithms that are easy to fall into local optimality,the w_BAPSO algorithm based on chaotic disturbance is proposed.In the cloud computing environment,linearly decreasing inertia weight with logistics chaotic disturbance is introduced.In the PSO update pro⁃cess,combining parameters such as bat pulse rate and pulse loudness,the w_BAPSO algorithm with chaotic disturbance is used in the cloud computing task scheduling process.The algorithm is applied to Cloudsim cloud computing simulation software for experimental verification.Test the effectiveness of w_BAPSO algorithm under different task scale conditions.Experimental results show that the chaotic disturbance w_BAPSO algorithm effectively reduces the time and cost of task scheduling in the process of cloud computing task scheduling.Therefore,the chaotic disturbance-based w_BAPSO algorithm proposed can not only improve the convergence speed and search accuracy of the algorithm,but also reduce the cost and time of cloud computing task scheduling,and improve the efficiency of task scheduling.