基于遗传算法的生物网络自适应负载平衡实现  

Genetic Algorithm-based Implementation of Load Balancing Adaptation for Bio-network

作　　者：丁永生[1] 张向锋[1] 任立红[1] 孙霏[1] 

机构地区：[1]东华大学信息科学与技术学院

出　　处：《系统仿真学报》2007年第6期1331-1334,共4页Journal of System Simulation

基　　金：国家自然科学基金重点项目(60534020);教育部新世纪优秀人才支持计划(NCET-04-415);教育部科技创新工程重大项目培育资金项目(706024);上海市国际科技合作基金项目(061307041)

摘　　要：自适应性网络环境将成为未来Internet的不可缺少的重要构成部分,而生物网络由分散的、自治、移动的个体组成,能够自我调整、适应和生存。在提出的生物网络框架中设计了一种特殊的生物实体——调度生物实体,利用调度实体来指导生物实体的移动,以期获得生物网络的负载平衡。然后提出了一种基于遗传算法的负载平衡算法,该算法以网络负载平衡为优化目标,使实体相对均衡地提供服务,达到合理利用生物网络资源,增强其自适应性的目的。最后,对网络服务使用进行仿真,实验结果证明了算法的有效性。Adaptive network environments will become an indispensable important component of future Intemet, while natural biological system is composed of dispersive, autonomous, and mobile biological individuals with self-regulation, adaptation, and survivability. Scheduling entities which are special bio-entities in the bio-network architecture were designed, and scheduling entities were utilized to guide migration of bio-entities in order to acquire load balancing of the bio-network. Also, a load balancing algorithm was proposed based on genetic algorithm. The algorithm aims at optimizing network load balancing and making bio-entities provide harmonically services to make full use of bio-network resource and enhance adaptation ofbio-network. Finally, network services utilization was simulated and the experiment results show the validity of the algorithm.

关 键 词：生物网络结构 调度生物实体 自适应性 负载平衡 遗传算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TP393.01[自动化与计算机技术—控制科学与工程]