混合CPU架构双态云平台缓存效率优化方法  

Cache efficiency optimization method for dual-state cloud platform based on hybrid CPU architecture

作　　者：陈瑞 冷迪 李英 CHEN Rui;LENG Di;LI Ying(Shenzhen Power Supply Bureau Co.,Ltd.,Shenzhen 518000,Guangdong Province,China)

机构地区：[1]深圳供电局有限公司,广东深圳518000

出　　处：《信息技术》2022年第5期148-153,共6页Information Technology

摘　　要：目前的混合CPU架构双态云平台缓存效率优化方法在优化过程中,只针对虚拟资源的服务质量进行分析,无法综合考量最短等待时间和资源负载均衡问题。为了解决上述问题,提出基于离散人工蜂群算法的混合CPU架构双态云平台缓存效率优化方法。引用离散人工蜂群算法,建立多目标数学模型,分析节点偏好满意度,通过搜索算子得到最佳的侦查蜂搜索方式,实现缓存划分完成程序优化。实验表明,基于离散人工蜂群算法的混合CPU架构双态云平台缓存效率优化方法能够有效提高缓存性能,在调度过程能够更好地改变系统性能,提高普适性。In the process of optimization,the current cache efficiency optimization methods of hybrid CPU architecture dual state cloud platform only focus on the quality of service of virtual resources,while ignoring comprehensive consideration of the shortest waiting time and resource load balancing.In order to solve the above problems,a cache efficiency optimization method based on discrete artificial bee colony algorithm for dual state cloud platform with hybrid CPU architecture is proposed.The bee colony search algorithm is used to set multi-target math model to analyze node preference satisfaction,and the optimization of the cache partition is completed by the best scout bee search algorithmn method gained by search operator.Experiment results show that the cache efficiency optimization method based on discrete artificial bee colony algorithm for hybrid CPU architecture dual state cloud platform can effectively improve the cache performance,better change the system performance in the scheduling process,therefore,improves the universality.

关 键 词：离散人工蜂群算法 混合CPU架构 双态云平台 缓存效率 优化方法 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]