采用改进二进制蝙蝠算法的任务调度算法

发布时间：2018-06-24 00:33

本文选题：任务调度 + 二进制蝙蝠算法　；参考：《西安交通大学学报》2017年10期

【摘要】：针对海服务系统环境中任务完成时间过长的问题,提出一种基于改进二进制蝙蝠算法(IBBA)的任务调度算法。该算法通过在二进制蝙蝠算法(BBA)寻优过程中引入非线性惯性权重因子,平衡全局搜索和局部搜索能力;利用2个不同的邻居蝙蝠算子构成扰动项,避免算法陷入局部最优;利用自适应学习因子调整全局最优算子和邻居蝙蝠算子的权重,控制整个寻优过程由全局搜索为主向局部搜索为主过渡。实验结果表明:IBBA可以稳定地搜索到全局最优值,与现有的基于二进制粒子群算法(BPSO)和二进制蝙蝠算法的任务调度算法相比,在任务数较多时,基于IBBA的任务调度算法能避免过早收敛,使任务完成时间显著减少。在海服务网络中,将该算法应用于任务调度,可提高处理大粒度服务的效率。
[Abstract]:A task scheduling algorithm based on improved binary bat algorithm (IBBA) is proposed to solve the problem of long task completion in the sea service system. By introducing a nonlinear inertia weight factor in the process of optimizing the binary bat algorithm (BBA), the algorithm balances the global search and local search capability, and uses 2 different neighbors. The bat operator constitutes a perturbation term to avoid the local optimal algorithm. The adaptive learning factor is used to adjust the weight of the global optimal operator and the neighborhood bat operator, and the whole optimization process is controlled by the global search mainly to the local search. The experimental results show that IBBA can search the global optimal value steadily and be based on the existing two. Compared with the task scheduling algorithm of the particle swarm optimization (BPSO) and the binary bat algorithm, the task scheduling algorithm based on IBBA can avoid premature convergence and reduce the task completion time significantly when the number of tasks is large. In the sea service network, the algorithm is applied to task scheduling, which can improve the efficiency of processing large granularity services.
【作者单位】：中国科学院声学研究所国家网络新媒体工程技术研究中心;中国科学院大学;
【基金】：国家高技术研究发展计划资助项目(2015AA015802)
【分类号】：TP18

【相似文献】