基于改进蚁群算法的负载均衡机制的研究

Research on Load Balancing Mechanism Based on Improved AOC

针对传统网络中集群负载不均、负载压力大等问题,提出一种基于改进蚁群算法的动态负载均衡机制。该算法可根据服务器性能动态调整负载调度方案,实现服务器集群最小响应时间下的最大资源利用率。论文在基本蚁群算法的模型上,针对蚁群算法前期收敛速度慢和后期容易陷入局部最优解等问题,结合遗传算法和伪随机序列对算法进行优化。最后经实验结果证明,改进的蚁群算法能更好地提升系统负载均衡性能,实现负载目标。

Aiming at the problems of uneven cluster load and heavy load pressure in traditional networks,a dynamic load balancing mechanism based on improved ant colony algorithm is proposed. The algorithm can dynamically adjust the load scheduling scheme according to the server performance to achieve the maximum resource utilization under the minimum response time of the server cluster. Based on the model of the basic ant colony algorithm,this paper optimizes the algorithm based on the slow convergence speed of the ant colony algorithm in the early stage and the tendency to fall into the local optimal solution in the later stage,combining genetic algorithm and pseudo-random sequence. Finally,the experimental results prove that the improved ant colony algorithm can better improve the system load balancing performance and achieve the load goal.