基于改进的布谷鸟算法在汽车系统电子节点负载均衡中的研究

Research of Electronic Node's Balanced Load in Automobile Electronic System Based on Improved Cuckoo Algorithm

汽车电子节点负载一直都是汽车电子系统中的研究重点,本文针对汽车电子任务负载不均衡的特点,引入布谷鸟算法,在该算法的基础引入高斯变异算子来处理每一个阶段中的鸟窝最佳位置的选择,然后通过反向学习的多样性因子对不同阶段中的鸟窝位置进行调整,通过改进后的算法使得寻找最优解的效率得到了提高。仿真实验证明本文算法在一定程度上提高汽车电子节点的任务资源分配效率,降低了节点资源分配的消耗。

Automobile electronic node load has always been the research focus in automobile electronic system. According to the automobile electronic task’s characteristics of imbalanced load, the author of this paper has introduced the cuckoo algorithm, based on which Gaussian mutation operator is introduced to select the optimal location of bird’s nest at every stage, then adjust the nest’s location at different stages through the diversity factor of reverse learning, and improve the efficiency of finding optimal solutions through the improved algorithm. Simulation experiments have proved that the algorithm proposed in this paper has to some extent improved the automobile electronic node’s efficiency of task resources allocation and reduced its consumption in resources allocation.