摘要
针对当前云网络中大数据稳定评测算法存在数据冗余度高、传输颗粒度不明显、传输性能较差等难题,提出了一种基于线性超混沌评估机制的云网络大数据稳定评测算法。首先,基于传输成本具有的维度特性进行稳定建模,设计了多维资源片的方式进行传输质量评测;其次,将数据传输中的质量维度,如传输带宽、包冗余度等纳入传输评测口径,且采取拉普拉斯质量评测算法对传输过程中的维度耗费进行特征指数建模,实现了云网络中大数据传输中的稳定评测,且评估效率较高。仿真实验表明,线性超混沌评估机制能够有效改善大数据传输中的拥塞现象,网络传输性能稳定。所提算法可以准确、稳定地评测云网络运行质量,且成本代价较低,实现过程较为便捷。
In order to solve the problem that large data stability evaluation algorithm in the current cloud network, such as high data redundancy, time-domain partition and poor transmission performance, this paper proposes a large data stability evaluation algorithm based on linear hyperchaos evaluation mechanism. First of all,for the stability characteristics of the transmission cost with dimensional modeling based on transmission quality evaluation through the transmission process of large size of data block; secondly, the quality dimension in data transmission, such as transmission bandwidth, packet redundancy and quality evaluation of caliber, take the Laplasse algorithm for feature index modeling of transmission process the dimensions of cost, to achieve a stable evaluation of large data transmission in the cloud network with high efficiency evaluation. The simulation results show that the mechanism can effectively improve congestion in large data transmission, network transmission performance is stable, and the noise immunity is superior.
作者
王艳
Wang Yan(Chuzhou Branch, Anhui Open University, Chuzhou 239000, Chin)
出处
《湖南文理学院学报（自然科学版）》
CAS
2018年第2期44-48,共5页
Journal of Hunan University of Arts and Science(Science and Technology)
关键词
云网络
数据评估
质量维度
联合评估
拉普拉斯质量评测
cloud network
data assessment
quality dimension
joint assessment
Laplasse quality evaluation
