Workload-aware request routing in cloud data center using software-defined networking

Large latency of applications will bring revenue loss to cloud infrastructure providers in the cloud data center. The existing controllers of software-defined networking architecture can fetch and process traffic information in the network. Therefore, the controllers can only optimize the network latency of applications. However, the serving latency of applications is also an important factor in delivered user-experience for arrival requests. Unintelligent request routing will cause large serving latency if arrival requests are allocated to overloaded virtual machines. To deal with the request routing problem, this paper proposes the workload-aware software-defined networking controller architecture. Then, request routing algorithms are proposed to minimize the total round trip time for every type of request by considering the congestion in the network and the workload in virtual machines（VMs）. This paper finally provides the evaluation of the proposed algorithms in a simulated prototype. The simulation results show that the proposed methodology is efficient compared with the existing approaches.

Virtual machine placement optimizing to improve network performance in cloud data centers

With the wide application of virtualization technology in cloud data centers, how to effectively place virtual machine （VM） is becoming a major issue for cloud providers. The existing virtual machine placement （VMP） solutions are mainly to optimize server resources. However, they pay little consideration on network resources optimization, and they do not concern the impact of the network topology and the current network traffic. A multi-resource constraints VMP scheme is proposed. Firstly, the authors attempt to reduce the total communication traffic in the data center network, which is abstracted as a quadratic assignment problem; and then aim at optimizing network maximum link utilization （MLU）. On the condition of slight variation of the total traffic, minimizing MLU can balance network traffic distribution and reduce network congestion hotspots, a classic combinatorial optimization problem as well as NP-hard problem. Ant colony optimization and 2-opt local search are combined to solve the problem. Simulation shows that MLU is decreased by 20%, and the number of hot links is decreased by 37%.

Enhancing Reliability via Checkpointing in Cloud Computing Systems

Cloud computing is becoming an important solution for providing scalable computing resources via Internet. Because there are tens of thousands of nodes in data center, the probability of server failures is nontrivial. Therefore, it is a critical challenge to guarantee the service reliability. Fault-tolerance strategies, such as checkpoint, are commonly employed. Because of the failure of the edge switches, the checkpoint image may become inaccessible. Therefore, current checkpoint-based fault tolerance method cannot achieve the best effect. In this paper, we propose an optimal checkpoint method with edge switch failure-aware. The edge switch failure-aware checkpoint method includes two algorithms. The first algorithm employs the data center topology and communication characteristic for checkpoint image storage server selection. The second algorithm employs the checkpoint image storage characteristic as well as the data center topology to select the recovery server. Simulation experiments are performed to demonstrate the effectiveness of the proposed method.

Review:Data center network architecture in cloud computing:review, taxonomy, and open research issues

The data center network(DCN), which is an important component of data centers, consists of a large number of hosted servers and switches connected with high speed communication links. A DCN enables the deployment of resources centralization and on-demand access of the information and services of data centers to users. In recent years, the scale of the DCN has constantly increased with the widespread use of cloud-based services and the unprecedented amount of data delivery in/between data centers, whereas the traditional DCN architecture lacks aggregate bandwidth, scalability, and cost effectiveness for coping with the increasing demands of tenants in accessing the services of cloud data centers. Therefore, the design of a novel DCN architecture with the features of scalability, low cost, robustness, and energy conservation is required. This paper reviews the recent research findings and technologies of DCN architectures to identify the issues in the existing DCN architectures for cloud computing. We develop a taxonomy for the classification of the current DCN architectures, and also qualitatively analyze the traditional and contemporary DCN architectures. Moreover, the DCN architectures are compared on the basis of the significant characteristics, such as bandwidth, fault tolerance, scalability, overhead, and deployment cost. Finally, we put forward open research issues in the deployment of scalable, low-cost, robust, and energy-efficient DCN architecture, for data centers in computational clouds.

强化学习云计算数据中心网络的智能路由策略

针对当前云计算数据中心网络大规模访问时,最优路由选择难造成的系统负载不均衡问题,提出人工智能强化学习算法的智能路由策略.以整个网络用户吞吐量最大化与数据中心网络传输成本最小化为优化目标,将路由选择问题表示为马尔可夫模型并通过智能体学习先前的历史经验求解最优传输路径,设计实时最优智能路由方案.在云计算数据中心网络Fat-tee中实验,表明此路由方案可以根据实时传输路径的传输能力实现有利于传输的智能路由,并且只需要较少的计算资源,实现了整个网络的负载均衡,并可以避免网络拥塞,平均吞吐量高于普通路由3倍多,在高负载下优势更加明显,保障了云计算数据中心网络的高效使用.

新一代云网融合数据中心关键技术研究

云网融合是通信技术和信息技术深度融合发展的必然趋势,国家政策、市场和技术等各方面推动着云网体系架构从云网协同向云网一体的融合架构演进。以云网融合为代表的新型数据中心是产业的发展方向,伴随着业务的拓展,迫切需要关键技术的革新。从云网融合数据中心演进趋势出发,阐述了新业务与新挑战,研究分析了新一代云网融合数据中心的关键技术。

面向云计算的数据中心网络体系结构设计

利用云计算技术构建分层次的数据中心网络体系结构,在互联网接入层接入互联网数据资源,通过核心汇聚层连接高性能路由器与接入交换机,并将接入层传来的数据传输业务接入层的服务器。在业务接入层中设计网络带宽分配方法,利用运营管理层实现数据中心网络体系结构日常维护功能。

基于VxLAN协议的新型SDN架构及应用

针对指挥信息系统云数据中心的传统网络架构存在的网络资源利用率不高、网络策略与业务无法自适应以及虚拟机迁移困难等问题,设计了一种基于虚拟扩展本地局域网(VxLAN)协议的新型软件定义网络(SDN)架构。分析了该架构的优势及信息处理流程,并以指挥信息系统双活云数据中心为例给出了该架构的应用效果。应用分析可见,该架构既可满足网络集中控制和网络服务质量适应差异化业务的需求,又可提升网络资源利用率、虚拟机跨域迁移能力以及指挥信息系统运行稳定性与可靠性。

云数据中心网络纵深防御探讨

近年来,云数据中心的运行安全问题遇到了一定的挑战。文章基于云数据中心网络安全服务需求,介绍分析了信息保障技术框架纵深防御,针对IATF纵深防御模型存在的不足,明确改进思路,借鉴纵深防御模型提出了主动型纵深防御模型的建设框架,并立足于网络假设、网络威胁、网络纵深防御架构、网络纵深防御技术架构4个维度,制订出网络纵深防御架构的设计方案,最后从合理性、实用性和先进性3个方面做出总结,明确云数据中心网络纵深防御具有实用价值,可以为云数据中心安全防护工作提供参考。

算力时代下数据中心发展趋势研究

数字经济的发展,新兴技术的应用,对算力基础设施提出更高的要求及挑战。数据中心作为算力服务的重要承载基础之一,基于算力时代背景介绍我国数据中心的发展现状特点及服务要求,分析数据中心布局规划的模型思考、算网协同的内涵特点、绿色低碳的目标要求等发展趋势。

基于改进灰色聚类算法的云架构数据中心网络异常流量过滤算法

为避免异常流量影响云架构数据中心网络安全运行,需要对云架构数据中心网络异常流量进行过滤。异常流量在不同信噪比和信道条件下过滤难度不同,为了在不同过滤条件下保障异常流量过滤效果,提出了基于改进灰色聚类算法的云架构数据中心网络异常流量过滤算法。通过时间-频率分析构建了云架构数据中心网络流量传输模型,采集网络流量序列;引入加权广义距离改进灰色聚类算法,利用改进的灰色聚类算法计算网络流量序列特征最佳聚类结果,实现流量序列特征提取;通过主成分分析法获取流量序列特征的主分量特征值,构建两个子空间,将流量特征以矩阵方式映射到两个子空间中;根据映射周期向量的平方预测误差与阈值计算结果,过滤异常流量。实验结果表明,该算法可通过聚类实现数据中心网络流量序列特征提取,在不同信噪比和信道条件下有效过滤异常流量;当网络信噪比为25dB且流量在高斯信道中传输时,异常流量过滤效果更突出。

网络云数据中心节能方案研究

为实现网络云数据机房节能降耗,有效降低运维成本中的电费支出,本文通过研究网络云业务特殊性及运维指标,分析网络云能耗构成要素,验证各因素对数据中心节电影响及对上云业务影响。根据能耗要素分析情况,本文提出了一种网络云资源池全景式节能方案,通过优化虚拟层资源调度实现资源适度集中,减少无效资源占用;通过设备综合节能措施实现设备级能耗灵活管控;通过机房/微模块/设备联动群控降低制冷能耗。本方案有效降低用电成本,实现增收减支,同时解决节电带来的资源冷启动和关联告警等问题,确保上云业务感知不下降。本方案已于数据中心网络云机房完成试验,试验期间每天节能5880 kW·h,并于数据中心内网络云大区完成全量应用,综合每年节约电费成本超440万元。

On Peer-Assisted Data Dissemination in Data Center Networks: Analysis and Implementation

Data Center Networks （DCNs） are the fundamental infrastructure for cloud computing. Driven by the massive parallel computing tasks in cloud computing, one-to-many data dissemination becomes one of the most important traffic patterns in DCNs. Many architectures and protocols are proposed to meet this demand. However, these proposals either require complicated configurations on switches and servers, or cannot deliver an optimal performance. In this paper, we propose the peer-assisted data dissemination for DCNs. This approach utilizes the rich physical connections with high bandwidths and mutli-path connections, to facilitate efficient one-to-many data dissemination. We prove that an optimal P2P data dissemination schedule exists for FatTree, a specially- designed DCN architecture. We then present a theoretical analysis of this algorithm in the general multi-rooted tree topology, a widely-used DCN architecture. Additionally, we explore the performance of an intuitive line structure for data dissemination. Our analysis and experimental results prove that this simple structure is able to produce a comparable performance to the optimal algorithm. Since DCN applications heavily rely on virtualization to achieve optimal resource sharing, we present a general implementation method for the proposed algorithms, which aims to mitigate the impact of the potentially-high churn rate of the virtual machines.

云数据中心网络安全服务架构及防范机制构建

文章以云数据中心为研究对象,阐述网络安全服务架构及防范机制构建,探究云数据中心网络安全服务架构面临的风险,分析其网络安全服务架构,并提出云数据中心网络安全服务架构的防范策略。

私有云在数据中心网络安全中的应用

为进一步提升数据中心网络运行的安全性,就要结合私有云特点落实规范化数据处理机制,建构更加科学、规范的服务平台,打造完整且合理可控的数据应用体系,为数据中心网络管理水平全面优化予以支持。文章分析了私有云的概念和发展现状,并从身份认证技术、信息传输技术、备份恢复技术、监控审计技术以及选择应用加密技术等方面对具体技术的应用要点展开讨论。

A cost-effective scheme supporting adaptive service migration in cloud data center

Cloud computing as an emerging technology promises to provide reliable and available services on de- mand. However, offering services for mobile requirements without dynamic and adaptive migration may hurt the performance of deployed services. In this paper, we propose MAMOC, a cost-effective approach for selecting the server and migrating services to attain enhanced QoS more econom- ically. The goal of MAMOC is to minimize the total operating cost while guaranteeing the constraints of resource de- mands, storage capacity, access latency and economies, including selling price and reputation grade. First, we devise an objective optimal model with multi-constraints, describing the relationship among operating cost and the above con- straints. Second, a normalized method is adopted to calculate the operating cost for each candidate VM. Then we give a de- tailed presentation on the online algorithm MAMOC, which determines the optimal server. To evaluate the performance of our proposal, we conducted extensive simulations on three typical network topologies and a realistic data center net- work. Results show that MAMOC is scalable and robust with the larger scales of requests and VMs in cloud environment. Moreover, MAMOC decreases the competitive ratio by identifying the optimal migration paths, while ensuring the constraints of SLA as satisfying as possible.

云计算数据中心网络安全风险及主动防御技术研究

为进一步提高云计算数据中心的网络安全性能,构建了一种软件定义网络(Software Defined Network,SDN)防火墙与入侵检测系统(Intrusion Detection System,IDS)联动的主动防御系统。该系统弥补了SDN防火墙与IDS的缺陷,SDN防火墙根据IDS识别恶意流量的特征,后期再有此类流量进入,会对恶意流量进行有效识别和阻断。结果表明,通过构建SDN防火墙与IDS联动的多维度主动防御架构,可以提高云计算数据中心抵御网络安全风险的能力。

公共卫生信息服务专有云数据中心建设与实践

目的:针对国内各类公共卫生服务数据中心云部署的迫切需求,探索专有云网端一体化建设的方法和思路。方法:整体规划业务全流程的云、网、端3个关键层面,从业务需求、总体思路、基础硬件、网络与安全、终端等方面综合设计和建设。结果:通过专有云数据中心模块化设计方式,建成适合公共卫生业务的数据中心。结论:建设专有云数据中心,实现自主可控、弹性扩展、长期稳定运行的整体目标,为公共卫生服务行业数据中心的云化建设和部署提供参考方案。

软件定义的云数据中心网络基础理论与关键技术

介绍了国家重点基础研究发展计划("973"计划)"软件定义的云数据中心网络基础理论与关键技术"项目的主要研究内容。指出了当前云数据中心网络所面临的挑战,并针对问题提出了利用软件定义网络的解决方案。对于软件定义的云数据中心网络未来发展需要研究的4个课题,即软件定义的云数据中心网络架构、云数据中心网络资源利用率优化、云数据中心网络多租户资源管理和云数据中心网络能耗协同控制,进行了论证和阐述。

基于SDN的跨数据中心承载技术

互联网产业的发展和云计算的兴起催生了跨数据中心互联的需求,而软件定义网络技术为解决数据中心互联的网络瓶颈提供了重要途径。首先介绍了几种常用的数据中心互联技术,分析了SDN的技术优势,然后提出了一种基于SDN的运营商数据中心互联承载技术方案,并阐述其实现思路。该方案可实现DC间的网络虚拟化,能够提供用户业务定制、网络自动开通、任意虚拟机间的策略隔离、流量调度、用户就近访问、DC间的容灾备份等业务功能。