摘要
云计算利用分布式系统进行复杂计算,其中的资源分配技术是当前的关注焦点,为了更好地提高云计算系统的服务效率,可以按照一定策略将各种资源分配给虚拟机,并充分考虑CPU内存、虚拟机放置能耗、性能损耗等约束条件,选择和应用优化的算法,即基于强化学习的虚拟机放置的基于强化学习的资源分配(Reinforcement Learning-based Resource Allocation,RLRA)算法和蒙特卡罗搜索树(Monte Carlo Tree Search,MCTS)算法,并进行系统资源的合理调整和动态分配,提高云计算系统的能耗节约效能。
Cloud computing uses distributed systems to perform complex calculations.The resource allocation technology is the current focus of attention.In order to better improve the service efficiency of the cloud computing system,various resources can be allocated to virtual machines according to certain strategies,and Fully consider the constraints such as CPU memory,virtual machine placement energy consumption,performance loss,etc.,select and apply optimized algorithms,namely,the virtual machine placement algorithm RLRA algorithm and MCTS algorithm based on reinforcement learning,and carry out reasonable adjustment and dynamic allocation of system resources.Improve the energy saving efficiency of the cloud computing system.
作者
刘勍
LIU Qing(Fuzhou Melbourne Polytechnic,Fuzhou Fujian 350000,China)
出处
《信息与电脑》
2021年第13期33-35,共3页
Information & Computer
关键词
云计算系统
资源分配技术
优化
cloud computing system
resource allocation technology
optimization
作者简介
刘勍(1991-),女,吉林公主岭人,硕士研究生,助教。研究方向:云计算、虚拟化。
