In the past two decades, software aging has been studied by both academic and industry communities. Many scholars focused on analytical methods or time series to model software aging process. While machine learning ha...In the past two decades, software aging has been studied by both academic and industry communities. Many scholars focused on analytical methods or time series to model software aging process. While machine learning has been shown as a very promising technique in application to forecast software state: normal or aging. In this paper, we proposed a method which can give practice guide to forecast software aging using machine learning algorithm. Firstly, we collected data from a running commercial web server and preprocessed these data. Secondly, feature selection algorithm was applied to find a subset of model parameters set. Thirdly, time series model was used to predict values of selected parameters in advance. Fourthly, some machine learning algorithms were used to model software aging process and to predict software aging. Fifthly, we used sensitivity analysis to analyze how heavily outcomes changed following input variables change. In the last, we applied our method to an IIS web server. Through analysis of the experiment results, we find that our proposed method can predict software aging in the early stage of system development life cycle.展开更多
Software-Defined Networking(SDN),with segregated data and control planes,provides faster data routing,stability,and enhanced quality metrics,such as throughput(Th),maximum available bandwidth(Bd(max)),data transfer(DT...Software-Defined Networking(SDN),with segregated data and control planes,provides faster data routing,stability,and enhanced quality metrics,such as throughput(Th),maximum available bandwidth(Bd(max)),data transfer(DTransfer),and reduction in end-to-end delay(D(E-E)).This paper explores the critical work of deploying SDN in large-scale Data Center Networks(DCNs)to enhance its Quality of Service(QoS)parameters,using logically distributed control configurations.There is a noticeable increase in Delay(E-E)when adopting SDN with a unified(single)control structure in big DCNs to handle Hypertext Transfer Protocol(HTTP)requests causing a reduction in network quality parameters(Bd(max),Th,DTransfer,D(E-E),etc.).This article examines the network performance in terms of quality matrices(bandwidth,throughput,data transfer,etc.),by establishing a large-scale SDN-based virtual network in the Mininet environment.The SDN network is simulated in three stages:(1)An SDN network with unitary controller-POX to manage the data traffic flow of the network without the server load management algorithm.(2)An SDN network with only one controller to manage the data traffic flow of the network with a server load management algorithm.(3)Deployment of SDN in proposed control arrangement(logically distributed controlled framework)with multiple controllers managing data traffic flow under the proposed Intelligent Sensing Server Load Management(ISSLM)algorithm.As a result of this approach,the network quality parameters in large-scale networks are enhanced.展开更多
Software rejuvenation is a recently proposed practive fault-tolerance approach to counteract software-aging phenomenon. Compared with clusters of a flat architecture, all the nodes share the same functions. The applic...Software rejuvenation is a recently proposed practive fault-tolerance approach to counteract software-aging phenomenon. Compared with clusters of a flat architecture, all the nodes share the same functions. The application of software rejuvenation on dispatcher-based web server farms is discussed, which employ rejuvenation both on the dispatcher and the worker pool. Stochastic reward net (SRN)models for time-based and prediction-based rejuvenation policies are constructed respectively and solved by stochastic Petri net package (SPNP). Numerical results show that appropriate rejuvenation strategies on the dispatcher and the worker pool could significantly reduce the expected downtime cost of the whole web server farm.展开更多
将分布式温室控制系统监控数据库系统划分成参数采集库、参数设定库、经济成本库、作物生态数据库以及设备管理库,并采用SQL Server 2000构建和管理温室环境监控数据库系统,介绍了开发这一系统的具体步骤、方法以及OLE DB和ADO的数据库...将分布式温室控制系统监控数据库系统划分成参数采集库、参数设定库、经济成本库、作物生态数据库以及设备管理库,并采用SQL Server 2000构建和管理温室环境监控数据库系统,介绍了开发这一系统的具体步骤、方法以及OLE DB和ADO的数据库应用编程。展开更多
以一所高校学生学籍管理系统的数据库设计为例,按照软件工程中结构化的分析与设计方法,对管理系统进行了需求分析,在此基础上对数据库进行了概念设计和逻辑结构设计,用SQL Server 2000进行了数据库物理设计与实现,给出了学生学籍管理系...以一所高校学生学籍管理系统的数据库设计为例,按照软件工程中结构化的分析与设计方法,对管理系统进行了需求分析,在此基础上对数据库进行了概念设计和逻辑结构设计,用SQL Server 2000进行了数据库物理设计与实现,给出了学生学籍管理系统数据库设计的全过程。展开更多
基金supported by the grants from Natural Science Foundation of China(Project No.61375045)the joint astronomic fund of the national natural science foundation of China and Chinese Academic Sinica(Project No.U1531242)Beijing Natural Science Foundation(4142030)
文摘In the past two decades, software aging has been studied by both academic and industry communities. Many scholars focused on analytical methods or time series to model software aging process. While machine learning has been shown as a very promising technique in application to forecast software state: normal or aging. In this paper, we proposed a method which can give practice guide to forecast software aging using machine learning algorithm. Firstly, we collected data from a running commercial web server and preprocessed these data. Secondly, feature selection algorithm was applied to find a subset of model parameters set. Thirdly, time series model was used to predict values of selected parameters in advance. Fourthly, some machine learning algorithms were used to model software aging process and to predict software aging. Fifthly, we used sensitivity analysis to analyze how heavily outcomes changed following input variables change. In the last, we applied our method to an IIS web server. Through analysis of the experiment results, we find that our proposed method can predict software aging in the early stage of system development life cycle.
文摘Software-Defined Networking(SDN),with segregated data and control planes,provides faster data routing,stability,and enhanced quality metrics,such as throughput(Th),maximum available bandwidth(Bd(max)),data transfer(DTransfer),and reduction in end-to-end delay(D(E-E)).This paper explores the critical work of deploying SDN in large-scale Data Center Networks(DCNs)to enhance its Quality of Service(QoS)parameters,using logically distributed control configurations.There is a noticeable increase in Delay(E-E)when adopting SDN with a unified(single)control structure in big DCNs to handle Hypertext Transfer Protocol(HTTP)requests causing a reduction in network quality parameters(Bd(max),Th,DTransfer,D(E-E),etc.).This article examines the network performance in terms of quality matrices(bandwidth,throughput,data transfer,etc.),by establishing a large-scale SDN-based virtual network in the Mininet environment.The SDN network is simulated in three stages:(1)An SDN network with unitary controller-POX to manage the data traffic flow of the network without the server load management algorithm.(2)An SDN network with only one controller to manage the data traffic flow of the network with a server load management algorithm.(3)Deployment of SDN in proposed control arrangement(logically distributed controlled framework)with multiple controllers managing data traffic flow under the proposed Intelligent Sensing Server Load Management(ISSLM)algorithm.As a result of this approach,the network quality parameters in large-scale networks are enhanced.
文摘Software rejuvenation is a recently proposed practive fault-tolerance approach to counteract software-aging phenomenon. Compared with clusters of a flat architecture, all the nodes share the same functions. The application of software rejuvenation on dispatcher-based web server farms is discussed, which employ rejuvenation both on the dispatcher and the worker pool. Stochastic reward net (SRN)models for time-based and prediction-based rejuvenation policies are constructed respectively and solved by stochastic Petri net package (SPNP). Numerical results show that appropriate rejuvenation strategies on the dispatcher and the worker pool could significantly reduce the expected downtime cost of the whole web server farm.
