基于优先级排列的内存数据库负载均衡仿真
Simulation of In-Memory Database Load Balancing Based on Priority Ranking
刘晓彤 1邓敦杰2
作者信息
- 1. 重庆城市科技学院人工智能与大数据学院,重庆 402100
- 2. 桂林电子科技大学海洋工程学院,广西 北海 536000
- 折叠
摘要
针对因云计算环境数据基数较大、数据种类过多、特征难提取,导致的数据储存比例失衡问题,提出一种内存数据库负载均衡优化算法.根据云计算环境下内存数据的数据特征、状态等参数,建立负载失衡问题模型,将存在问题的数据代入,求得负载率和虚拟资源参数关联变化.考虑到云计算环境下数据基数过大、数据离散性强的问题,将内存数据看作为分布复杂的资源网络,数据点看作网络节点,求解节点跟随网络状态发生的位置、速度以及状态更改,建立数据负载率的位置与更新速度规则,求解不同数据的负载均衡尺度,并排列优先级顺序,采集内存数据库参数输入至负载尺度函数中求解,根据每个数据点的最新负载尺度实行重新配比调整,完成均衡优化.实验结果表明,所提方法的负载均衡优化效率和效果较好,环境适应能力强.
Abstract
Aiming at the problem of imbalanced data storage ratio caused by big databases,excessive data types and difficult feature extraction in cloud computing environments,this article proposed a load balancing optimization al-gorithm for memory databases.According to the characteristics and status of memory data in cloud computing environ-ments,we built a model about load imbalance,and put the problematic data into it to obtain the correlation change be-tween load rate and virtual resource parameter.Considering that the base of big data was too large and the discrete-ness of data was too strong in cloud computing environments,we regarded the memory data as a complex resource net-work and treated the distributed data points as network nodes.Then,we solved the changes of position,speed and state of nodes following the network state.Moreover,we determined the position of the data load rate and established the update speed rules.Furthermore,we calculated the load balancing scales of different data and arranged them in priority order.Finally,we collected the parameters of the memory database and input them into the load-scale function for a solution.According to the latest load scale of the data point,we performed the reassembly and adjust-ment,thus completing the balanced optimization.Experimental results show that the proposed method has better effi-ciency and effect on load balancing optimization,as well as strong environmental adaptability.
关键词
云计算环境/内存数据库/负载均衡优化/虚拟资源/负载失衡Key words
Cloud computing environment/Memory database/Load balancing optimization/Virtual resources/Load imbalance引用本文复制引用
出版年
2024
NETL
NSTL
万方数据