摘要
为均衡网络负载,提高网络节点工作性能,建立了基于遗传模拟退火算法的网络负载均衡数学模型,提出将遗传模拟退火算法应用于寻优网络负载均衡的算法GSAA。OPNET仿真实验表明,GSAA算法将遗传算法和模拟退火算法相结合,发挥了遗传算法的快速全局搜索性能和模拟退火算法的局部搜索效率,显著地提高了搜索效率,能够高效地寻优均衡网络负载的参数。
In order to balance network loading and improve network performance, GSAA as a new network loading balance arithmetic is proposed. GSAA combines simulated annealing algorithm with genetic algorithm to optimize network loading balance. OPNET simulation experiment result shows that GSAA algorithm provides fast overall situation search capability of genetic algorithm and partial search efficiency of simulated annealing algorithm, the network loading balance performance is greatly improved
出处
《计算机与数字工程》
2008年第9期16-18,共3页
Computer & Digital Engineering
关键词
网络负载均衡
作业调度
遗传算法
退火算法
network loading balance, task scheduling, genetic algorithm, simulated annealing algorithm
