VMPlanner: Optimizing virtual machine placement and traffic flow routing to reduce network power costs in cloud data centers

In recent years, the power costs of cloud data centers have become a practical concern and have attracted significant attention from both industry and academia. Most of the early works on data center energy efficiency have focused on the biggest power consumers (i.e., computer servers and cooling systems), yet without taking the networking part into consideration. However, recent studies have revealed that the network elements consume 10–20% of the total power in the data center, which poses a great challenge to effectively reducing network power cost without adversely affecting overall network performance. Based on the analysis on topology characteristics and traffic patterns of data centers, this paper presents a novel approach, called VMPlanner, for network power reduction in the virtualization-based data centers. The basic idea of VMPlanner is to optimize both virtual machine placement and traffic flow routing so as to turn off as many unneeded network elements as possible for power saving. We formulate the optimization problem, analyze its hardness, and solve it by designing VMPlanner as a stepwise optimization approach with three approximation algorithms. VMPlanner is implemented and evaluated in a simulated environment with traffic traces collected from a data center test-bed, and the experiment results illustrate the efficacy and efficiency of this approach.     

A loan default discrimination model using cost-sensitive support vector machine improved by PSO

This study proposes a novel PSO–CS-SVM model that hybridizes the particle swarm optimization (PSO) and cost sensitive support vector machine (CS-SVM) to deal with the problem of unbalanced data classification and asymmetry misclassification cost in loan default discrimination problem. Cost sensitive learning is applied to the standard SVM by integrating misclassification cost of each sample into standard SVM and PSO is employed for parameter determination of the CS-SVM. Meantime, the financial data are discretized by using the self-organizing mapping neural network. And the evaluation indices are reduced without information loss by genetic algorithm for decreasing the complexity of the model. The effectiveness of integrated model of CS-SVM and PSO is verified by three experiments comparing with traditional CS-SVM, PSO–SVM, SVM and BP neural network through real loan default data of companies in China. The corresponding results indicate that the accuracy rate, hit rate, covering rate and lift coefficient are improved dramatically by the developed approach. The proposed method can control the different types of errors distribution with various cost of misclassification accurately, reduce the total misclassification cost largely, and distinguish the loan default problems effectively.     

物联网环境下基于B／S模式的监控系统

论文针对区域范围大,管理监控困难和成本高的问题,提出了一种基于物联网技术的,对远端环境变量进行监管和远程控制的实时监控系统。该系统使用B／S模式,实现可非固定式对环境情况的监控;基于Struts2框架搭建系统,实现M、V、c的逻辑分离,以及对监控参数按需修改和方便扩展;使用DAO模式对系统的持久层进行实现;Ajax技术结合jQuery框架,对前端结果进行无刷新式的更新,从而实现无需在中控机房对远程环境进行监控的系统。系统连接短信平台,可随时把异常情况发送给紧急联络人,有利于第一时间采取措施解决问题。本系统具有良好的可扩展性和可移植性,非常便于投入使用和各种扩展功能的实现。     

OMNET的安装与版本间区别

随着信息技术的进步与发展,无线传感器网络(WSN)在无线通信技术中占有着举足轻重的地位,在诸如环境监测、医疗护理、军事领域有着广泛的应用,其综合了传感器技术、无线通信技术等技术,是当前国际上备受关注的前沿热点研究领域.本文主要研究现阶段经典的路由算法,并对其进行了仿真实现,时LEACH算法进行了改进,降低无线传感器网络节点能耗,延长无线传感器网络节点的寿命,提高整个网络的工作效率.     

网站安全管理经验浅析

互联网作为信息双向交流和通讯的工具,已经成为信息的传播重要媒介,被称之为继广播、报纸、电视后的第五种媒体--数字媒体,而网站作为它的一种体现形式,提供了一个对外的信息窗口,当然在提供对外的同时,相应地就面临了一个问题,那就是网站的安全问题.在网站建设后,针对网站的安全问题,本文根据实际经验,对网站安全管理的措施进行浅析.     

基于Web的企业人才数据库研究和应用

管理员后台管理、权限审核、动态呈现等技术,为技术人员选拔及人才统计提供数据基础,促进了企业的信息化建设。     

基于微粒群抽样的关联规则算法

采用了ApASAR算法的设计思想,符合最小范围下界的将会进入后选集进一步判断是否是频繁规则,不断更新,在候选规则集中加入新的规则组合,并将候选集中表现突出的规则组合晋升至大项集中,而将无法进入候选规则集的规则组合淘汰。     

网上银行系统性能测试小记

在交易量不断增长的情况下,X银行原有的个人网上银行系统从架构到性能都无法满足当前的需求,在这种情况下,X银行计划对原有的网上银行系统进行优化和升级.     

基于多环QFT的高超声速飞行器鲁棒控制

阐述了定量反馈理论(QFT)的基本原理和设计方法,针对超燃冲压发动机不同工作状态时高超声速飞行器不确定性模型,应用多环QFT设计了高超声速飞行器纵向飞行控制系统;仿真结果表明,运用QFT方法设计的控制系统不仅具有良好的跟踪性能和抗干扰性能,而且能够很好地解决飞行控制系统由于模型参数具有不确定性而造成的控制系统鲁棒性设计问题,并从工程应用角度为高超飞行器纵向飞行控制系统提供了一种鲁棒控制设计方案。     

高精度二相混合式步进电机控制系统研究

在二相混合式步进电机数学模型的基础上,针对电机低速运行时的振动和噪声过大的问题,研究了正弦脉宽调制细分驱动技术,开发出一种新型的基于单片机的多细分二相混合式步进电机驱动器。该系统主要分为数字控制部分、GAL片逻辑综合信号处理单元、SG3525恒流控制电路、驱动功放电路、过流保护及反馈电路和系统供电电源模块等。系统采用专用集成芯片和可编程逻辑器件,以8位单片机AT89C2051为控制核心,实现恒流控制、正/反转运行、过流保护和多档位细分等功能。实验结果表明,系统硬件和软件设计合理可行,各项技术指标均达到了设计要求。