改进的量子遗传算法在网络拥塞控制中的应用

摘要

当前以遗传算法为基础的网络拥塞控制方法对网络拥塞存在控制目标选取耗时，最优目标参数选取不均等问题，控制效果不佳。针对这一问题，结合量子计算的优点，提出一种基于改进量子遗传算法的网络拥塞控制算法，首先对网络拥塞的原理进行分析，建立QoS路由拥塞控制数学模型，将量子计算引入遗传算法进行改进，在静态旋转角的量子遗传算法的基础上，保证拥塞目标参数的选取准确性，给出算法的实现方法和具体流程。实验结果表明，该算法的搜索速度快、效率高、可以很好地优化网络性能，实现拥塞控制。%Since the current network access and congestion control method based on the genetic algorithm has poor control effect such as time⁃consuming target selection and optimal target's parameters selection,a network congestion control algorithm based on the improved quantum genetic algorithm is proposed in combination with the advantage of quantum computation. The principle of network congestion is analyzed. QoS routing congestion control mathematical model is established. The genetic algo⁃rithm,introducing quantum computation,is improved to guarantee the accuracy of the selection of congestion target parameters on the basis of the static rotation angle of quantum genetic algorithm. The implementation method and the specific process of the algorithm is given. The test results show that the algorithm has fast search speed and high efficiency,can optimize the network performance in a good way,and achieve the goal of congestion control.