基于自适应蜂群算法的云计算负载平衡机制

针对将蜂群算法应用在负载平衡系统中,出现的由于请求之间关系处理不当而产生的不利于负载平衡的资源局部密集现象,提出了改进的自适应蜂群算法。通过引进其他类型的请求,以阻断短时间内本该到来的与该服务器处理的请求有某些相似的请求,由此增强了负载平衡的可用性,提高了系统吞吐量。实验结果表明基于蜂群算法的负载平衡机制无论是在系统吞吐量方面或是系统可扩展性方面均适用于云计算环境,改进的自适应蜂群算法在系统吞吐量方面较传统算法性能提高5%以上。

Load balancing strategy of cloud computing based on adaptive artificial bee colony algorithm

When Artificial Bee Colony(ABC) algorithm is applied to the load balancing system,local intensive resources may arise due to improper handling of the relationship between requests.Therefore,an improved adaptive ABC algorithm was proposed.By introducing other types of requests,the request accumulation of the similar type got blocked.Then,not only the availability but also the system throughput had been improved.The experimental results show that either the system throughput or the scalability of the load balancing mechanism based on ABC algorithm,is applicable to cloud computing environments.The improved adaptive ABC algorithm is superior to traditional algorithms more than 5% in system throughput.