一种混合遗传算法在云计算负载均衡中的应用研究

遗传算法(GA)被广泛用于解决科学与工程中的复杂问题,然而传统的GA在求解高维函数优化问题时存在很多限制因素,因此无法在云计算中直接应用.提出了一种多智能体与遗传算法混合的多Agent遗传算法(MAGA).首先论证了MAGA较传统GA的优越之处,然后采用MAGA建立了基于虚拟化资源管理的负载均衡模型,解决云计算中的负载均衡问题.与Min_min策略对比实验结果表明,多Agent遗传算法能够达到更加优越的负载均衡效果.

Application of a hybrid genetic algorithm in the load balancing of cloud computing

Genetic algorithm is widely applied in solving the complicated scientific and engineering problems.But because there are many limiting factors in the application of traditional GA in solving the optimization of multi-dimension function,the traditional GA algorithm can not applied to cloud computing.Multi-agent genetic algorithm(MAGA) is a hybrid algorithm of GA with multi-agents,whose performance is far superior to that of the traditional GA.The advantages of MAGA over traditional GA are demonstrated,and then MAGA is used for solving the load balancing in cloud computing by designing a load balancing model on the basis of virtualization resource management.Finally,the experiment results prove that MAGA is able to achieve better performance of load balancing than Min_min strategy.