基于遗传算法的生物网络自适应负载平衡实现

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。

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

Adaptive network environments will become an indispensable important component of future Internet, 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 of bio-network. Finally, network services utilization was simulated and the experiment results show the validity of the algorithm.