基于改进萤火虫算法的云计算负载均衡研究

Load Balancing for Cloud Computing based on Improved Glowworm Swarm Algorithm

提出了改进的萤火虫优化算法,运用于解决云环境下资源负载均衡的问题.该算法改进了决策域半径的更新,能够有效地克服精确度不高、后期收敛较慢的缺点.利用这个优势,全面地考虑资源节点的负载指标,建立虚拟化资源管理负载模型,更改目标函数,实现云计算资源的平均负载.通过仿真验证,表明该算法能够提高资源利用率,可以在较短的时间内达到较好的负载均衡效果.

An improved glowworm swarm optimization algorithm is proposed and used to solve problems of load balancing in cloud computing. The improving methods on updating decision-domain radius can overcome previ- ous shortcomings of low accuracy and slow convergence rate in later period to achieve the purposes of load balancing, and taking advantage of its features, while considering load indicators totally and modeling virtual resource loads as one part of the objective function. The ultimate experiment results show that this algorithm can improve resource utilization and attain the desired effect of load balancing well in short time.