基于免疫量子进化算法的负载均衡策略  

Load Balancing Strategy Based on Immune Quantum Evolutionary Algorithm

作　　者：苏日娜[1] 王宇[1] 

机构地区：[1]宁波工程学院电子与信息工程学院,浙江宁波315016

出　　处：《计算机工程》2011年第2期154-156,共3页Computer Engineering

基　　金：浙江省自然科学基金资助项目(Y1080123);浙江省教育厅基金资助项目(Y201016215)

摘　　要：在集群系统任务调度和分配中,提出一种基于免疫量子进化算法的负载均衡策略。该策略采用量子化编码和量子进化操作优化任务分配,在量子陷入局部极值下,引入免疫操作进行接种疫苗和免疫选择,从而增加种群多样性。仿真结果表明,与SGALB策略相比,该策略具有更高的搜索效率,其集群系统的整体性能更优。In the task scheduling and allocation of cluster system, this paper presents a load balancing strategy based on Immune Quantum Evolutionary Algorithm（IQEA）. This strategy optimizes load distribution by quantum coding and quantum ew）lution operator. It ensures the diversity of population by using immune operator vaccinations and immune selection when quantum is into the local extremum. Simulation result shows that this strategy has higher search efficiency than the SGALB strategy, and it can improve the whole performance of cluster system effectively.

关 键 词：免疫量子进化算法 集群系统 负载均衡 调度器 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]