摘要
对云计算中数据流的存储负载均衡进行优化,能够提高数据流在网内存储分布的均匀性。优化数据流的负载均衡,需要对数据流存储节点的负载情况进行评估,将高强度负载转移到负载较轻的节点上,完成数据流存储负载均衡的优化。传统方法先对数据流存储路径进行最优选取,解决存储负载高维耦合问题,但忽略了高强度负载至轻负载节点的转移,导致优化效果差。提出基于蛇形时隙的云计算中数据流存储负载均衡优化方法。采用蛇形时隙算法划分数据流网格,设定网格内数据流存储负载优先级。将高优先级数据流存储至距离查询节点较近的网络区域;采用多阈值预测机制评估低优先级数据流存储节点的负载情况。利用动态虚拟坐标机制将高强度负载转移至负载较轻的节点上,实现云计算中数据流存储负载均衡的优化。实验结果表明,所提方法使数据流在网内存储分布更加均匀,提高了云计算服务质量,减少了数据传输能耗。
In this paper, we present a method to optimize load balancing for data flow storage in cloud computing based on snakelike slot time. Firstly, we used the snakelike slot time algorithm to divide data flow grid and set priority level of data stream storage load in the grid. Then, we stored high priority data stream in the network region near to the query node. Meanwhile, we used the multi - threshold prediction mechanism to assess the load status of storage node in the low priority data stream. Moreover, we used dynamic virtual coordinate mechanism to transfer the high strength load to the node with light load. Thus, we achieved the optimization of data stream storage load balance in cloud computing. Simulation results show that the proposed method can make data flow distributed in network more evenly, which improves the quality of cloud computing service and reduces the energy consumption in data transmission.
作者
叶伦强
YE Lun - qiang(Southwest Minzu University, Siehuan Chengdu 610225, China)
出处
《计算机仿真》
北大核心
2018年第10期246-249,共4页
Computer Simulation
基金
基于虚拟化的民族高校慕课云架构研究--以西南民族大学为例(2015NZYQN40)
关键词
云计算
数据流
存储
负载均衡
优化
Cloud computing
Data stream
Storage
Load balancing
Optimization
