Cost-Aware Multi-Domain Virtual Data Center Embedding

Virtual data center is a new form of cloud computing concept applied to data center. As one of the most important challenges, virtual data center embedding problem has attracted much attention from researchers. In data centers, energy issue is very important for the reality that data center energy consumption has increased by dozens of times in the last decade. In this paper, we are concerned about the cost-aware multi-domain virtual data center embedding problem. In order to solve this problem, this paper first addresses the energy consumption model. The model includes the energy consumption model of the virtual machine node and the virtual switch node, to quantify the energy consumption in the virtual data center embedding process. Based on the energy consumption model above, this paper presents a heuristic algorithm for cost-aware multi-domain virtual data center embedding. The algorithm consists of two steps: inter-domain embedding and intra-domain embedding. Inter-domain virtual data center embedding refers to dividing virtual data center requests into several slices to select the appropriate single data center. Intra-domain virtual data center refers to embedding virtual data center requests in each data center. We first propose an inter-domain virtual data center embedding algorithm based on label propagation to select the appropriate single data center. We then propose a cost-aware virtual data center embedding algorithm to perform the intra-domain data center embedding. Extensive simulation results show that our proposed algorithm in this paper can effectively reduce the energy consumption while ensuring the success ratio of embedding.

Metaverse virtual social center for elderly communication in time of social distancing

Background The lack of social activities among the elderly due to physical limitations can result in loneliness and depression. The spread of COVID-19 has made it difficult for the elderly to conduct stable social activities, increasing feelings of loneliness. The metaverse is a virtual world that mirrors reality. This allows the elderly to overcome the constraints of reality and perform social activities stably and continuously, providing new ideas for alleviating loneliness. Methods By analyzing their needs, a virtual social center framework for the elderly was proposed in this study. In addition, a prototype system was designed according to this framework. The elderly can socialize in virtual reality with metaverse-related technologies and human–computer interaction tools. Additionally, a test was conducted jointly with the chief physician of the geriatric rehabilitation department of a tertiary hospital. Results The results demonstrated that the mental state of the elderly who had used the virtual social center was significantly better than that of those who had not used it. Conclusions Thus, virtual social centers can help relieve loneliness and depression among the elderly with increasing global epidemics and an aging society. Hence,they have promotional value.

基于System Center的校园私有云设计

随着云计算技术的发展,出现了多种云计算模型。私有云是比较适合在高校中应用的部署模型。微软的System Center由多个组件构成,为私有云部署提供了从基础架构到服务门户的一整套管理工具,是学校信息化建设中有效的解决方案。

Traffic-Aware VDC Embedding in Data Center： A Case Study of FatTree

Virtualization is a common technology for resource sharing in data center. To make efficient use of data center resources, the key challenge is to map customer demands （modeled as virtual data center, VDC） to the physical data center effectively. In this paper, we focus on this problem. Distinct with previous works, our study of VDC embedding problem is under the assumption that switch resource is the bottleneck of data center networks （DCNs）. To this end, we not only propose relative cost to evaluate embedding strategy, decouple embedding problem into VM placement with marginal resource assignment and virtual link mapping with decided source-destination based on the property of fat-tree, but also design the traffic aware embedding algorithm （TAE） and first fit virtual link mapping （FFLM） to map virtual data center requests to a physical data center. Simulation results show that TAE＋FFLM could increase acceptance rate and reduce network cost （about 49% in the case） at the same time. The traffie aware embedding algorithm reduces the load of core-link traffic and brings the optimization opportunity for data center network energy conservation.

Multi-Dimensional Aware Scheduling for Co-optimizing Utilization in Data Center

Resource Scheduling is crucial to data centers. However, most previous works focus only on one-dimensional resource models which ignoring the fact that multiple resources simultaneously utilized, including CPU, memory and network bandwidth. As cloud computing allows uncoordinated and heterogeneous users to share a data center, competition for multiple resources has become increasingly severe. Motivated by the differences on integrated utilization obtained from different packing schemes, in this paper we take the scheduling problem as a multi-dimensional combinatorial optimization problem with constraint satisfaction. With NP hardness, we present Multiple attribute decision based Integrated Resource Scheduling (MIRS), and a novel heuristic algorithm to gain the approximate optimal solution. Refers to simulation results, in face of various workload sets, our algorithm has significant superiorities in terms of efficiency and performance compared with previous methods.

A hardware-based algorithm for virtual machine provisioning in a private cloud

Cloud computing is becoming a key factor in the market day by day. Therefore, many companies are investing or going to invest in this sector for development of large data centers. These data centers not only consume more energy but also produce greenhouse gases. Because of large amount of power consumption, data center providers go for different types of power generator to increase the profit margin which indirectly affects the environment. Several studies are carried out to reduce the power consumption of a data center. One of the techniques to reduce power consumption is virtualization. After several studies, it is stated that hardware plays a very important role. As the load increases, the power consumption of the CPU is also increased. Therefore, by extending the study of virtualization to reduce the power consumption, a hardware-based algorithm for virtual machine provisioning in a private cloud can significantly improve the performance by considering hardware as one of the important factors.

Data Center Network Architecture

1 Introduction The history of data centers can be traced back to the 1960s. Early data centers were deployed on main- frames that were time-shared by users via remote terminals. The boom in data centers came duringthe internet era. Many companies started building large inter- net-connected facililies,

基于MR技术的智能配送中心虚拟仿真实训平台教学实践研究

随着信息技术的发展,传统物流管理正在演进到与数字化智能技术深度融合的智能物流新阶段,将混合现实技术(MR)应用于虚拟仿真实训平台建设,解决物流管理专业实训教学三高三难问题,激发学生获取专业知识和技能的兴趣,本研究通过在《配送中心运营管理》课程应用MR技术搭建虚拟仿真实训平台,进行数字化教学改革实践为例,对智慧供应链专业群的实训教学条件建设、教学过程设计、教学资源开发、教学效率的提升进行了有益的探索,希望为高职实训教学提供有效的教学参考。

Optimised Migrate Virtual Machine Rejuvenation

Server virtualization is an essential component in virtualized software infrastructure such as cloud computing. Virtual machines are generated through a software called virtual machine monitor (VMM) running on physical servers. The risks of software aging caused by aging-related bugs affect both VM and VMM. As a result, service reliability degrades may generate huge financial losses to companies. This paper presents an analytic model using stochastic reward nets for time-based rejuvenation techniques of VMM and VM. We propose to manipulate the VM behavior while the VMM rejuvenation is according to the load on the system. Using a previous Petri net model of virtualized server, we performed an algorithm in order to optimize rejuvenation technique and achieve high availability. So we perform Migrate-VM rejuvenation or Warm-VM rejuvenation while there are current jobs in the system. Although Migrate-VM rejuvenation is better than Warm-VM rejuvenation in steady state availability, it can’t be always performed as it depends on the capacity of the other host. When the queue is empty and the virtual machine has no current jobs to serve, we propose to combine both VMM rejuvenation and VM rejuvenation. We show that the proposed technique can enhance the availability of VMs.

新工科背景下化工虚拟仿真实训中心建设

在新工科背景下虚拟仿真技术融合到化工实践教学中可以有效解决实践教学困难,淮北师范大学化工专业通过强化师资队伍、更新教学理念和探索过程性考核等举措不断深化虚拟仿真中心建设。虚拟仿真的引入有助于提高本科生的创新精神、工程能力和安全意识,满足化工行业需求的创新型技术人才,为提高本科教学质量提供有力保障。

大学英语课程虚拟教研室建设的理论和实践研究

大学英语课程虚拟教研室是适应新时代大学英语教学特征,纾解大学英语教学难题的重要途径。本质上,大学英语课程虚拟教研室是基于现代信息技术平台,开展跨区、跨校协同学、教、研的课程基层教学组织,按功能可分为课程群类、专题教研类、学科服务类,其建设既要遵循虚拟教研室一般的共性要求,又要符合大学英语课程自身建设的要求,实践层面应该着力在课程共享和教研协同上下功夫。既有大学英语课程虚拟教研室起到了很好的示范作用,但在学科服务和平台融合方面仍需努力。

国家级实验教学示范中心建设中虚实结合实践课程的探索与实践——以化学化工国家级实验教学示范中心(安徽大学)为例

化学化工国家级实验教学示范中心(安徽大学)以培养具有社会责任感,富于人文情怀、科学精神和国际视野,服务国家和区域经济社会发展的高素质创新人才为培养目标,在工程专业认证和新工科建设的背景下,中心积极推进虚实结合实践类课程的建设。通过模拟生产现场真实场景,提升了师生互动效率,更好地实现了对学生创新能力、团队协作能力和工程实践能力的培养。中心虚实结合实践类课程的建设也解决了化工及相关专业实习的难点和痛点。

新工科背景下外语类虚拟教研室建设研究

新工科背景下外语类虚拟教研室是信息时代新型基层教学组织,探索新工科背景下外语类虚拟教研室建设,有助于提升工科院校外语教学质量和教学研究水平,更好地适应信息化时代和高等教育高质量发展对外语教学的新要求。面向G16联盟的全国部分以工为主地方应用型本科院校外语类虚拟教研室建设,以立德树人、资源协作共享、多元发展和“智能+”技术赋能为基本原则,打造数字化为支撑的网络化新型校本课程教研形态、协同构建“外语+应用型工程人才”培养模式、共建共享外语类校本课程、建立教师发展成长规划的建设内涵、基于TCSCOG运行模式提出“3+2+1”的外语类虚拟教研室建设机制与运行模式、评价标准。实践证明,面向G16联盟的外语类虚拟教研室运行效果良好,可以为面向工科专业的外语类虚拟教研室建设提供有益借鉴。

虚拟教研室内涵、运行现状及建设对策探析

在传统基层教学组织日渐式微背景下,虚拟教研室在“智能+”信息化时代开始大规模建设,信息化、基层教学组织、协同教研新形态是虚拟教研室的3个主要特征。国家级虚拟教研室的建设探索概括为搭建平台、召开工作会议、共建优质资源、开展教师培训和建立评价监测机制5点。最后,从加强学校顶层设计、聚焦特色分类发展、整合资源发挥协同作用、建立结合学科特色的评价监测和激励机制4个方面提出加强虚拟教研室建设的对策,为各学校虚拟教研室的建设提供参考。

高等职业技术学院云机房设计及优势探讨

本文通过分析高等职业技术学院传统机房使用中存在维护工作量大、投资费用高、资源利用低等诸多问题,提出了利用云计算技术来解决传统机房不足之处。通过云机房方案设计,采用分布式存储系统,提出整体架构由基础框架、管理软件、桌面控制器、终端接入设备构成,并总结了云机房部署灵活、运维方便、随时教学、安全高效的优势,最后结合实际分析了云机房网络依赖性高、终端处理能力弱、专业性软件适应性差等问题。

云计算中心的高效地震处理解释能力体系建设与工业化应用

随着云计算中心硬件环境的建立,如何充分利用云中心的计算、存储和网络基础设施环境建立高效的地震处理解释能力体系,从而实现地震处理解释新技术的大规模推广与工业化应用成为必须解决的问题。文章将重点介绍如何利用云计算中心的基础设施环境,建设高效地震处理解释能力体系。

XR虚拟实训中心的设计人才培养模式改革思路

随着虚拟现实等数字智能技术的发展,以实训中心为依托的实训教学面临着新的机遇和话语体系。为了明晰XR虚拟现实技术如何助力设计人才培养,文章通过虚拟实训中心建设与研究现状、内驱责任、人才培养思路和积极价值四个方面的探讨,提出实训教学数智化思维转变,建构有效助力应用型高校的实训课程,并总结依托虚拟实训中心的设计人才培养的方法论措施,旨在分析依托虚拟实训中心的设计类人才培养的规律,定位其教学角色,推动智能时代虚拟实训中心教学模式改革。

“以学生为中心,以矿业为特色”的工程力学虚拟仿真一流课程建设与实践

面向国家能源开发领域,立足于巷道工程有关的岩石力学前沿问题,创设了“以学生为中心,以矿业为特色”的工程力学虚拟仿真实验教学课程,构建了以教学目标为引导、以实验模块为主线、以实验内容为应用的课程体系,坚持“以学生为中心”的教学理念,采用多样化的教学方式,构建了沉浸式、体验式、探究式的学习场域,完善了开放共享的信息化实验教学新模式和新体系。课程建设与实践表明,本虚拟仿真实验课程有利于培养学生家国情怀、能源特质、创新思维和工程实践能力。

面向电量-调频-容量市场的数据中心园区算力及电力资源规划

数据中心广泛建设是智能时代的发展趋势。如何在保证数据中心服务质量的前提下,考虑数据中心负荷转移特性,并对其进行合理规划,对降低数据中心规划总成本及提升新型电力系统灵活性均有显著意义。为此,提出一种考虑多元电力市场引导下的数据中心园区算力及电力资源优化规划方法。首先,通过多面体定界收缩法建立虚拟发电机和虚拟储能模型,描述数据中心园区的聚合可调特性。然后,根据不同电力市场的结算规则,研究了数据中心园区参与电量-调频-容量市场的方式和经济收益。在此基础上,以综合成本最小化为目标,优化数据中心园区发电机、储能的建设容量以及服务器的建设数量。最后,以阿里巴巴公开运行数据为例,证明考虑多元电力市场能够大大降低数据中心规划成本,激励数据中心园区投资建设更多灵活性资源,为电网提供有效的调频服务和容量支撑。

基于数字孪生的数据中心机房设备耗电可视化监控系统设计

为提升数据中心机房设备耗电监控效果及可视化监控系统的实时性,提出基于数字孪生的数据中心机房设备耗电可视化监控系统设计。首先,在数字孪生技术的基础上完成系统架构及功能的设计;其次,构建源数据矩阵,计算矩阵的欧氏距离,并通过K-means聚类算法实现设备耗电的聚类处理;最后,利用数字孪生技术将映射真实物理车间到虚拟车间,引入孪生实体概念表达机房部件,融合数据中心机房设备故障数据,构建网络神经模型训练样本数据,生成新的故障诊断模型,实现基于数字孪生的数据中心机房设备耗电可视化监控。结果表明,所提方法的数据中心机房设备耗电监控系统的可视化效果好、设备耗电监控结果好,可为数据管理提供可靠的技术支撑。