Seamless Configuration of Virtual Network Functions in Data Center Provider Networks

Network function virtualization has enabled data center providers to offer new service provisioning models. Through the use of data center management software (cloud managers), providers allow their tenants to customize their virtual network infrastructure, enabling them to create a network topology that includes network functions (e.g., routers, firewalls), either chosen among the natively supported catalog or provided by third-parties. In order to deploy a ready-to-go service, providers have also to take care of pushing functional configurations into each network function (e.g., IP addresses for routers and policy rules in firewalls). This paper proposes an architecture that extends current cloud management software to enable the configuration of network functions. We propose a model-based approach that exploits the use of additional software components, i.e. translators and gateways, which are network function-agnostic, i.e. they are vendor-neutral and not specific for a particular type of network function, and do not require any change in the network functions. A prototype of this solution has been also implemented and tested, in order to validate our approach and evaluate its effectiveness in the configuration phase.     

网络功能虚拟化下服务功能链的资源管理研究综述

伴随着云计算,软件定义网络和网络功能虚拟化等网络新技术的出现,未来网络运维向着虚拟化、智能化的方向不断迈进.网络功能虚拟化提供了一种服务节点虚拟化的方法,它采用通用服务器替代传统网络中的专用中间件,可以大大降低网络运营商的建设和运营成本,提升网络管理的灵活性和可扩展性.由于网络端到端服务通常需要不同的服务功能,采用虚拟化技术构建网络服务功能链,进行资源的合理分配和调度成为一个重要的研究课题,引起了学术界和工业界的广泛关注.从网络功能虚拟化的技术背景出发,介绍了网络功能虚拟化下服务功能链资源管理的基础架构、技术基础和应用场景.而后基于服务功能链编排的不同阶段,将现有理论研究划分为4个部分:组链、部署、调度和按需缩放分别展开论述,从问题出发介绍和分析了研究现状.最后,针对现有存在问题,提出了一些拟解决方案,并对未来的研究方向进行了展望.     

A cost‐efficient resource provisioning algorithm for DHT‐based cloud storage systems

Personal cloud storage provides users with convenient data access services. Service providers build distributed storage systems by utilizing cloud resources with distributed hash table (DHT), so as to enhance system scalability. Efficient resource provisioning could not only guarantee service performance, but help providers to save cost. However, the interactions among servers in a DHT‐based cloud storage system depend on the routing process, which makes its execution logic more complicated than traditional multi‐tier applications. In addition, production data centers often comprise heterogeneous machines with different capacities. Few studies have fully considered the heterogeneity of cloud resources, which brings new challenges to resource provisioning. To address these challenges, this paper presents a novel resource provisioning model for service providers. The model utilizes queuing network for analysis of both service performance and cost estimation. Then, the problem is defined as a cost optimization with performance constraints. We propose a cost‐efficient algorithm to decompose the original problem into a sub‐optimization one. Furthermore, we implement a prototype system on top of an infrastructure platform built with OpenStack. It has been deployed in our campus network. Based on real‐world traces collected from our system and Dropbox, we validate the efficiency of our proposed algorithms by extensive experiments. Copyright © 2016 John Wiley & Sons, Ltd.     

A hybrid wavelet decomposer and GMDH-ELM ensemble model for Network function virtualization workload forecasting in cloud computing

Nowadays Network function virtualization (NFV) has drawn immense attention from many cloud providers because of its benefits. NFV enables networks to virtualize node functions such as firewalls, load balancers, and WAN accelerators, conventionally running on dedicated hardware, and instead implements them as virtual software components on standard servers, switches, and storages. In order to provide NFV resources and meet Service Level Agreement (SLA) conditions, minimize energy consumption and utilize physical resources efficiently, resource allocation in the cloud is an essential task. Since network traffic is changing rapidly, an optimized resource allocation strategy should consider resource auto-scaling property for NFV services. In order to scale cloud resources, we should forecast the NFV workload. Existing forecasting methods are providing poor results for highly volatile and fluctuating time series such as cloud workloads. Therefore, we propose a novel hybrid wavelet time series decomposer and GMDH-ELM ensemble method named Wavelet-GMDH-ELM (WGE) for NFV workload forecasting which predicts and ensembles workload in different time-frequency scales. We evaluate the WGE model with three real cloud workload traces to verify its prediction accuracy and compare it with state of the art methods. The results show the proposed method provides better average prediction accuracy. Especially it improves Mean Absolute Percentage Error (MAPE) at least 8% compared to the rival forecasting methods such as support vector regression (SVR) and Long short term memory (LSTM).     

云计算环境中SaaS的接入控制和调度策略研究

SaaS是一种基于网络的软件应用模式,是服务提供商将应用软件统一部署在自己的服务器上,用户根据自己的实际需要,通过互联网向服务提供商订购并支付自己所需的服务。在未来,SaaS模式是占主导地位的云服务模型。文中阐述SaaS的基本概念,介绍了SaaS的参考结构以及服务流程,分析概括了不同类型的服务要求的接人控制策略,总结了不同性能要求作业的调度策略,最后结合已有的云计算环境下的SaaS接入控制和调度策略研究成果,展望了未来的研究方向和亟待解决的关键问题。     

Cost optimal scheduling in IaaS for dependent workload with particle swarm optimization

Optimizing cloud provisioning for scientific workflow applications is a challenging problem, since the workflows generally contain dependency between tasks and require specific deadlines. Usually, cloud providers offer many options to the consumers. These options include the number of virtual machines, the type of each virtual machine and the purchasing method for each machine. Currently, cloud provisioning cost optimization is an active research topic. Most of this literature is concerned with task scheduling, cloud option selection, and cloud option selection for scientific workflow applications. However, research that attempts to find solutions which cover both cloud option selection and workflow task scheduling is very limited. In this paper, we focus on optimizing the cost of purchasing infrastructure-as-a-service cloud capabilities to achieve scientific work flow execution within the specific deadlines. The proposed system considers the number of purchased instances, instance types, purchasing options, and task scheduling as constraints in an optimization process. Particle swarm optimization augmented with a variable neighborhood search technique is used to find the optimal solution. Our approach finds the configurations of purchasing options with the optimum budget for a specified workflow application based on the required performance. The solutions from the proposed system show promising performance from the perspectives of the total cost and fitness convergence when compared with other state-of-the-art algorithms.     

一种基于干扰估计的虚拟功能服务链创建及部署方法

针对网络功能虚拟化中服务链性能受到负载干扰的问题,提出一种考虑虚拟功能间干扰的虚拟功能服务链部署方法。首先,基于CPU利用率和I/O带宽对虚拟功能干扰度进行估计;然后,构建虚拟功能部署和链路创建模型,从链路速率、节点数量、延迟等角度提出了服务链部署优化目标;最后,以干扰度估计结果为依据,根据模拟退火思想提出一种服务链功能组合和选择方法,并利用部署模型将链路实例化。实验结果表明,和现有方法相比,本文方法能够有效提高服务链的执行性能并满足部署优化目标。     

面向云应用系统的容错即服务优化提供方法

通过提供高效且持续可用的容错服务以保障云应用系统的可靠运行是至关重要的.采用容错即服务的模式,提出了一种优化的云容错服务动态提供方法,从云应用组件的可靠性及响应时间等方面描述云应用容错需求,以常用的复制、检查点和NVP（N-version programming）等容错技术为基础,充分考虑容错服务动态切换开销,分别针对支撑容错服务的底层云资源是否足够的场景,给出可用容错即服务提供方案的最优化求解方法.实验结果表明,所提方法降低了云应用系统支付的容错服务费用及支撑容错服务的底层云资源的开销,提高了容错服务提供商为多个云应用实施高效、可靠容错即服务的能力.     

网络功能虚拟化技术综述

无论是企业网还是数据中心,为实现相关应用功能、提升网络性能和加强网络安全等部署了大量的网络功能设备,但这些网络功能设备大多基于硬件,存在功能固化、扩展能力差、统一管理困难等问题。为解决上述问题,学术界和工业界不约而同将目光投向了网络功能虚拟化NFV技术。通过解耦网络功能和物理设备,使网络功能不受物理设备的约束,便于网络设备服务的升级更新,同时,NFV为新的体系结构、系统和应用的产生提供了可能。首先介绍了NFV技术,并与云计算和SDN进行对比,然后从VNF的系统结构、数据平面、控制平面、部署方式、实现语言和应用6个维度详细阐述了当前的研究成果,最后总结并展望了NFV未来的研究发展方向。     

OPTIMIS: A holistic approach to cloud service provisioning

We present fundamental challenges for scalable and dependable service platforms and architectures that enable flexible and dynamic provisioning of cloud services. Our findings are incorporated in a toolkit targeting the cloud service and infrastructure providers. The innovations behind the toolkit are aimed at optimizing the whole service life cycle, including service construction, deployment, and operation, on a basis of aspects such as trust, risk, eco-efficiency and cost. Notably, adaptive self-preservation is crucial to meet predicted and unforeseen changes in resource requirements. By addressing the whole service life cycle, taking into account several cloud architectures, and by taking a holistic approach to sustainable service provisioning, the toolkit aims to provide a foundation for a reliable, sustainable, and trustful cloud computing industry.     

Towards an autonomic performance management approach for a cloud broker environment using a decomposition–coordination based methodology

Efficient resource allocation of computational resources to services is one of the predominant challenges in a cloud computing environment. Furthermore, the advent of cloud brokerage and federated cloud computing systems increases the complexity of cloud resource management. Cloud brokers are considered third party organizations that work as intermediaries between the service providers and the cloud providers. Cloud brokers rent different types of cloud resources from a number of cloud providers and sublet these resources to the requesting service providers. In this paper, an autonomic performance management approach is introduced that provides dynamic resource allocation capabilities for deploying a set of services over a federated cloud computing infrastructure by considering the availability as well as the demand of the cloud computing resources. A distributed control based approach is used for providing autonomic computing features to the proposed framework via a feedback-based control loop. This distributed control based approach is developed using one of the decomposition–coordination methodologies, named interaction balance, for interactive bidding of cloud computing resources. The primary goals of the proposed approach are to maintain the service level agreements, maximize the profit, and minimize the operating cost for the service providers and the cloud broker. The application of interaction balance methodology and prioritization of profit maximization for the cloud broker and the service providers during resource allocation are novel contributions of the proposed approach.     

Interconnecting ISP networks

The Internet is rife with paradox. For example, new optical switches capable of forwarding terabits of data (in photonic format) must work with a decades-old protocol suite first developed for software-controlled electronic packet switches. Another example is that while IP multicast offers by far the most efficient delivery vehicle for large-scale multiparty communications, few service providers deploy it, choosing instead to consume bandwidth and host resources with multiple point-to-point connections. One of the most interesting Internet-related paradoxes is the relationship between Internet service providers. While competing very publicly for customers using price, value-add services, and performance as leverage, they must privately cooperate among themselves to provide global connectivity. Indeed, without this cooperation each ISP network might devolve into its own separate world with few or none of the global Internet's benefits. Fortunately, this is not the case; in fact, the Internet is a network of networks-a mesh of separately controlled, interconnected networks that form one large, global entity     

基于网格的NGN增值业务生成框架

下一代网络（NGN）最大的特点之一是具备强大的增值业务提供能力，如何快速有效地生成、部署新的增值业务是当前研究的热点。该文以开放业务规范Parlay／OSAAPI为基础，探讨了基于网格技术的NGN增值业务生成框架，以实现多网络融合的灵活业务生成，并以一个第3方呼叫业务为例进行了说明。     

创建软件定义网络中的进程级纵深防御体系结构

云计算因其资源的弹性和可拓展性,在为用户提供各项服务时,相对于传统方式占据了先机。在用户考虑是否转向云计算时,一个极其重要的安全风险是：攻击者可以通过共享的云资源对云用户发起针对虚拟机的高效攻击。虚拟机作为云服务的基本资源,攻击者在攻击或者租用了某虚拟机之后,通过在其中部署恶意软件,并针对云内其他虚拟机发起更大范围的攻击行为,如分布式拒绝服务型攻击。为防止此种情况的发生,提出基于软件定义网络的纵深防御系统,以及时检测可疑虚拟机并控制其发出的流量,抑制来自该虚拟机的攻击行为并减轻因攻击所受到的影响。该系统以完全无代理的非侵入方式检测虚拟机状态,且基于软件定义网络,对同主机内虚拟机间或云主机间的网络流量进行进程级的监控。实验结果表明了该系统的有效性。     

SLA-based operations of massively multiplayer online games in clouds

Successful massively multiplayer online games (MMOGs) have today millions of registered users and hundreds of thousands of active concurrent players. To be able to guarantee quality of service (QoS) to a highly variable number of concurrent users, game operators statically over-provision a large infrastructure capable of sustaining the game peak load, even though a large portion of the resources is unused most of the time. To address this problem, we introduce in this work a new MMOG ecosystem for hosting and provisioning of MMOGs which effectively splits the traditional monolithic MMOG companies into three main service providers: game providers, game operators, and resource providers. Their interaction is regulated through comprehensive service level agreements (SLA) that establish the price, terms of operation, and compensation for service violations. In our model, game operators efficiently provision resources for MMOGs from multiple cloud providers, based on dynamic load forecasts, and ensure proper game operation that maintains the required QoS to all clients under varying resource availability. Game providers manage multiple distributed MMOGs for which they lease services under strict operational SLAs from game operators to satisfy all client requests. These three self-standing, smaller, more agile service providers enable access to the MMOG market for the small and medium enterprises, and to the current commercial cloud providers. We evaluate, through simulations based on real-life MMOG traces and commercial cloud SLAs, the impact of resource availability on the QoS offered to the MMOG clients. We find that our model can mitigate the negative effects of resource failures within four minutes and that MMOG server consolidation can accentuate the negative effects of failures in a resource-scarce environment. We further investigate different methods of ranking MMOG operational offers with either single or multiple (competing) MMOG providers. Our results show that compensations for SLA faults in the offer selection process can lead up to 11–16 % gain in the game providers’ income. We also demonstrate that adequate ranking of offers can lead to MMOG operational cost reductions from 20 up to 60 %.     

面向云计算的数据中心网络体系结构设计

近年来,云计算技术的蓬勃发展为整个IT行业带来了巨大变革.传统数据中心网络拓扑构建方式及网络层控制平面的运行机制存在固化性,已经难以满足新形势下日益增长的高性能及高性价比需求,并且无法支持云环境下更加灵活的按带宽租赁数据中心网络的运营方式.因此,提出了一种通过低造价的可编程交换机来构建具有高连通性的非树状数据中心网络的方式,并设计了可编程交换机与服务器2.5层代理协同工作的基于凸优化的虚拟网络带宽控制管理机制,从而提供足够的灵活性以对资源虚拟化技术提供更好的支持.实验表明,新型体系结构在降低构建成本的同时大幅提高了数据中心网络的吞吐量并提供了更加灵活的网络带宽分配机制.     

Using Policies to Manage Composite Web Services

When no single Web service can fulfil a user's request, providers often turn to composite Web services. However, developing a composite Web service is not simple and deploying the composition specification at runtime consists of several processes. Developers and deployers of composite Web services can use policies in various scenarios, from the announcement of Web services to the compatibility between Web services and composite Web services. Mapping guidelines for a Web service's behavior to policies can ensure an individual Web service's smooth engagement into a composite Web service     

Joint study on VMs deployment,assignment and migration in geographically distributed data centers

Enterprises build private clouds to provide IT resources for geographically distributed subsidiaries or product divisions. Public cloud providers like Amazon lease their platforms to enterprise users, thus, enterprises can also rent a number of virtual machines (VMs) from their data centers in the service provider networks. Unfortunately, the network cannot always guarantee stable connectivity for their clients to access the VMs or low-latency transfer among data centers. Usually, both latency and bandwidth are in unstable network environment. Being affected by background traffics, the network status can be volatile. To reduce the latency uncertainty of client accesses, enterprises should consider the network status when they deploy data centers or rent virtual data centers from cloud providers. In this paper, we first develop a data center deployment and assignment scheme for an enterprise to meet its users’ requirements under uncertain network status. To accommodate to the changes of the network status and users’ demands, a VMs migration-based redeployment scheme is adopted. These two schemes work in a joint way, and lay out a framework to help enterprises make better use of private or public clouds.