Today, in the field of computer networks, new services have been developed on the Internet or intranets, including the mail server, database management, sounds, videos and the web server itself Apache. The number of s...Today, in the field of computer networks, new services have been developed on the Internet or intranets, including the mail server, database management, sounds, videos and the web server itself Apache. The number of solutions for this server is therefore growing continuously, these services are becoming more and more complex and expensive, without being able to fulfill the needs of the users. The absence of benchmarks for websites with dynamic content is the major obstacle to research in this area. These users place high demands on the speed of access to information on the Internet. This is why the performance of the web server is critically important. Several factors influence performance, such as server execution speed, network saturation on the internet or intranet, increased response time, and throughputs. By measuring these factors, we propose a performance evaluation strategy for servers that allows us to determine the actual performance of different servers in terms of user satisfaction. Furthermore, we identified performance characteristics such as throughput, resource utilization, and response time of a system through measurement and modeling by simulation. Finally, we present a simple queue model of an Apache web server, which reasonably represents the behavior of a saturated web server using the Simulink model in Matlab (Matrix Laboratory) and also incorporates sporadic incoming traffic. We obtain server performance metrics such as average response time and throughput through simulations. Compared to other models, our model is conceptually straightforward. The model has been validated through measurements and simulations during the tests that we conducted.展开更多
针对云服务器中存在软件老化现象,将造成系统性能衰退与可靠性下降问题,借鉴剩余使用寿命(Remaining useful life,RUL)概念,提出基于支持向量和高斯函数拟合(Support vectors and Gaussian function fitting,SVs-GFF)的老化预测方法.首...针对云服务器中存在软件老化现象,将造成系统性能衰退与可靠性下降问题,借鉴剩余使用寿命(Remaining useful life,RUL)概念,提出基于支持向量和高斯函数拟合(Support vectors and Gaussian function fitting,SVs-GFF)的老化预测方法.首先,提取云服务器老化数据的统计特征指标,并采用支持向量回归(Support vector regression,SVR)对统计特征指标进行数据稀疏化处理,得到支持向量(Support vectors,SVs)序列数据;然后,建立基于密度聚类的高斯函数拟合(Gaussian function fitting,GFF)模型,对不同核函数下的支持向量序列数据进行老化曲线拟合,并采用Fréchet距离优化算法选取最优老化曲线;最后,基于最优老化曲线,评估系统到达老化阈值前的RUL,以预测系统何时发生老化.在OpenStack云服务器4个老化数据集上的实验结果表明,基于RUL和SVs-GFF的云服务器老化预测方法与传统预测方法相比,具有更高的预测精度和更快的收敛速度.展开更多
文摘Today, in the field of computer networks, new services have been developed on the Internet or intranets, including the mail server, database management, sounds, videos and the web server itself Apache. The number of solutions for this server is therefore growing continuously, these services are becoming more and more complex and expensive, without being able to fulfill the needs of the users. The absence of benchmarks for websites with dynamic content is the major obstacle to research in this area. These users place high demands on the speed of access to information on the Internet. This is why the performance of the web server is critically important. Several factors influence performance, such as server execution speed, network saturation on the internet or intranet, increased response time, and throughputs. By measuring these factors, we propose a performance evaluation strategy for servers that allows us to determine the actual performance of different servers in terms of user satisfaction. Furthermore, we identified performance characteristics such as throughput, resource utilization, and response time of a system through measurement and modeling by simulation. Finally, we present a simple queue model of an Apache web server, which reasonably represents the behavior of a saturated web server using the Simulink model in Matlab (Matrix Laboratory) and also incorporates sporadic incoming traffic. We obtain server performance metrics such as average response time and throughput through simulations. Compared to other models, our model is conceptually straightforward. The model has been validated through measurements and simulations during the tests that we conducted.
文摘针对云服务器中存在软件老化现象,将造成系统性能衰退与可靠性下降问题,借鉴剩余使用寿命(Remaining useful life,RUL)概念,提出基于支持向量和高斯函数拟合(Support vectors and Gaussian function fitting,SVs-GFF)的老化预测方法.首先,提取云服务器老化数据的统计特征指标,并采用支持向量回归(Support vector regression,SVR)对统计特征指标进行数据稀疏化处理,得到支持向量(Support vectors,SVs)序列数据;然后,建立基于密度聚类的高斯函数拟合(Gaussian function fitting,GFF)模型,对不同核函数下的支持向量序列数据进行老化曲线拟合,并采用Fréchet距离优化算法选取最优老化曲线;最后,基于最优老化曲线,评估系统到达老化阈值前的RUL,以预测系统何时发生老化.在OpenStack云服务器4个老化数据集上的实验结果表明,基于RUL和SVs-GFF的云服务器老化预测方法与传统预测方法相比,具有更高的预测精度和更快的收敛速度.
