A thermal-aware VM consolidation mechanism with outage avoidance

Efficient energy and temperature management techniques are essential elements for operators of cloud data centers. Dynamic virtual machine (VM) consolidation using live migration techniques presents a great opportunity for cloud service providers to adaptively reduce energy consumption and optimize their resource utilization. In recent studies, power consumption readings of individual physical hosts were chosen as the main monitoring parameters in their allocation policies, whereas very few have considered host temperature, which has shown to have a negative impact on server reliability, as a migration criterion. In this work, a thermal-aware VM consolidation mechanism is proposed for resource allocation optimization and server reliability assurance. We consider the variability in host temperature as a migration criterion to avoid outage incidents via having better VM consolidations. Extensive simulation results obtained from CloudSim show the promising performance of the proposed mechanism in energy saving while reducing the number of server outage incidents due to fluctuations in host temperature.     

安全的半监督方法的协同过滤推荐算法

为解决传统协同过滤算法中用户评分数据稀疏性,忽视物品及用户特征,所带来的推荐质量下降的问题,提出了一种基于安全的、高置信度的半监督方法的协同过滤推荐算法,采用安全的,高置信度的半监督方法S4VM对没有评分的数据进行有效预测,同时考虑用户的行为信息以及物品及用户特征。通过对未评分数据进行预测,能够有效地缓解数据的稀疏性,从而提高寻找最近邻的准确度。实验结果表明,该算法能够有效地提高系统的推荐质量。     

虚拟机迁移系统网络连接重定向技术*

针对虚拟机（virtual machine,VM）在不同子网间进行在线迁移时,因网络接入点发生改变而无法继续通信的问题,设计和实现了基于代理移动IP（proxy mobile IP,PMIP）的网络连接重定向系统。当VM迁移到外部子网时,将其看做移动节点,不改变IP地址,通过外部网络和家乡网络之间的双向隧道传输所有来自和发往该VM的网络数据。此方案中跨子网的在线迁移行为对VM以及与VM通信的节点透明。实验证明了该系统可以保证VM较快的网络切换速度和较好的网络通信性能。     

虚拟生产线框架及其实现

提出虚拟生产线基本框架结构及其实现方法,研究开放式系统结构和面向对象方法,开发出虚拟生产线实例模型。     

系统性试验与数据积累是拟实制造的基础

虚拟制造（VM）是虚拟现实（VR）技术在制造领域中的发展和应用，本文以VM技术的目标出发，强调虚拟原形与现实物量产品之间的“拟实度”是VM技术能否取得成功的关键，论述了建模和仿真技术在VM中的重要性，并提出了在生产中进行系统性试验和数据积累是建立VM系统的基础。     

基于时间窗的锌钡白转窑煅烧过程在线优化建模

应用混合核函数的最小二乘支持矢量机(LS-SVM)解决锌钡白转窑煅烧过程的多变量模型拟合问题,模型拟合精度高,效果好。为使系统实现模型参数的在线修正运算,扩展了LS-SVM,提出了一种基于KKT判定条件的时间窗在线建模算法。这一算法在时间窗向前移动的同时,依靠KKT判定条件,确定是否需要对新增的样本数据进行重新训练,避免不必要的重复运算。随着时间窗向前移动,系统不断更新模型参数,以适应工况变化的需要。仿真分析说明,这种建模方法在此类煅烧过程控制和产品质量提高上有着广阔的应用前景。     

温度对VM110SS套管钢在酸性环境中腐蚀行为的影响

模拟川东某气田气井封隔器失效后套管面临的腐蚀环境,利用自制高温高压釜进行VM110SS套管钢在总压18MPa、CO2分压0.54MPa、H2S分压0.41MPa、温度30~150℃条件下的腐蚀实验,得出了该气井工况下温度对VM110SS套管钢腐蚀速率的影响。采用扫描电镜和电子能谱分析方法对试样表面腐蚀产物形貌及成分进行分析。结果表明,VM110SS钢的平均腐蚀速率随温度的升高呈现先增大后减小的规律,气液相腐蚀速率最大值出现在90℃。在90℃气相中腐蚀速率为0.838mm/a、液相中腐蚀速率为1.130mm/a,发生极严重腐蚀。所有实验温度条件下,试样均发生均匀腐蚀,且腐蚀产物以硫铁化合物为主。本实验为酸性气田在不同井深及温度条件下套管的腐蚀状况评估提供了参考。     

基于运动轨迹分析的启发式木马检测系统

针对主动防御技术检测准确率不高的问题,提出了一种基于运动轨迹分析的启发式木马检测系统。提出了两种典型的木马运动轨迹,利用运动轨迹上的行为数据,结合判定规则与算法,实现对可疑文件危险等级的检测。实验结果表明,该系统检测未知木马性能优于传统方法,并且能够检测一些特殊木马。     

Virtual machine selection and placement for dynamic consolidation in Cloud computing environment

Dynamic consolidation of virtual machines (VMs) in a data center is an effective way to reduce the energy consumption and improve physical resource utilization. Determining which VMs should be migrated from an overloaded host directly influences the VM migration time and increases energy consumption for the whole data center, and can cause the service level of agreement (SLA), delivered by providers and users, to be violated. So when designing a VM selection policy, we not only consider CPU utilization, but also define a variable that represents the degree of resource satisfaction to select the VMs. In addition, we propose a novel VM placement policy that prefers placing a migratable VM on a host that has the minimum correlation coefficient. The bigger correlation coefficient a host has, the greater the influence will be on VMs located on that host after the migration. Using CloudSim, we run simulations whose results let draw us to conclude that the policies we propose in this paper perform better than existing policies in terms of energy consumption, VM migration time, and SLA violation percentage.     

云计算环境下软硬件节能和负载均衡策略

针对云计算服务环境下软硬件节能和负载均衡优化问题,提出一种自适应的云计算环境下虚拟机(VM)动态迁移软节能策略。该策略采用常用的硬件能耗感知技术——动态电压频率调节(DVFS)来实现分段优化的系统部件静态节能,又通过VM在线迁移技术实现云平台的动态自适应软件节能。在CloudSim云仿真平台下对比实现DVFS静态节能和自适应负载均衡的软节能策略,经PlanetLab云平台监测数据验证,结果表明：软硬结合的自适应能耗感知策略能够高效节能96%; DVFS+MAD_MMT节能策略(采用平均绝对偏差算法判定主机是否超载,基于最短迁移时间(MMT)原则选择VM移出)