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Transport network function virtualization

JOURNAL OF LIGHTWAVE TECHNOLOGY 2015年第8期33卷 1557-1564页

作者： Vilalta, Ricard Munoz, Rauel Mayoral, Arturo Casellas, Ramon Martinez, Ricardo Lopez, Victor Lopez, Diego Ctr Tecnol Telecomun Catalunya Barcelona 08860 Spain Telefon I D Barcelona 08019 Spain

In this paper, we present a network function virtualization (NFV) architecture to deploy different virtualized network functions (VNF) on an optical transport network. NFV concepts do not only apply to data plane functions (i.e., packet processing or forwarding), but also to control plane functions, such as path computation. First, we focus on the IT and network resources that are virtualized to provide the required VNFs. Second, we provide an example of VNF on top of the virtualized infrastructure, by proposing a path computation element (PCE) architecture to deploy a PCE by means of NFV. The instances of the virtualized PCE are deployed on demand, but they are perceived as a single-network element. We present the benefits of such approach by providing experimental validation.

关键词： Cloud and network orchestration GMPLS network function virtualization NFV orchestration and management openDaylight openStack path computation element

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NFV-Throttle: An Overload Control Framework for network function virtualization

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IEEE TRANSACTIONS ON network AND SERVICE MANAGEMENT 2017年第4期14卷 949-963页

作者： Cotroneo, Domenico Natella, Roberto Rosiello, Stefano Federico II Univ Naples Dept Elect Engn & Informat Technol I-80125 Naples Italy Critiware Srl I-80121 Naples Italy

network function virtualization (NFV) aims to provide high-performance network services through cloud computing and virtualization technologies. However, network overloads represent a major challenge. While elastic cloud computing can partially address overloads by scaling on-demand, this mechanism is not quick enough to meet the strict high-availability requirements of "carrier-grade" telecom services. Thus, in this paper we propose a novel overload control framework (NFV-Throttle) to protect NFV services from failures due to an excess of traffic in the short term, by filtering the incoming traffic toward virtual network functions (VNFs) to make the best use of the available capacity, and to preserve the QoS of traffic flows admitted in the network. Moreover, the framework has been designed to fit the service models of NFV, including VNFaaS and NFVIaaS. We present an extensive experimental evaluation on the NFV-oriented Clearwater IMS, showing that the solution is robust and able to sustain severe overload conditions with a very small performance overhead.

关键词： Overload control network function virtualization NFVIaaS VNFaaS cloud computing IP multimedia subsystem

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State of the Art and Research Challenges in the Security Technologies of network function virtualization

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IEEE INTERNET COMPUTING 2020年第1期24卷 25-35页

作者： Wu, Xiaochun Hou, Kaiyu Leng, Xue Li, Xing Yu, Yinbo Wu, Bo Chen, Yan Zhejiang Gongshang Univ Hangzhou Peoples R China Northwestern Univ Evanston IL USA Northwestern Univ Dept Elect Engn & Comp Sci Evanston IL USA Zhejiang Univ Comp Sci & Technol Hangzhou Peoples R China Zhejiang Univ Coll Comp Sci & Technol Hangzhou Peoples R China Wuhan Univ Sch Elect Informat Wuhan Peoples R China Tsinghua Univ Beijing Peoples R China

In recent years, network function virtualization (NFV) has drawn considerable attention due to its potential for service agility and low total cost of ownership. As the core of an NFV implementation, security issues in the management and control platform must be comprehensively addressed-from architectural concept to deployment. In this article, we first analyze the state of the security architecture based on ETSI-NFV, and then propose useful security practices for an NFV-based management and control ecosystem. To encourage future research, we also identify the ongoing research challenges and open security issues relevant to the NFV.

关键词： Computer security Computer architecture Monitoring network function virtualization Hardware Ecosystems network function virtualization Service chain Microservice Virtualized network function

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Enabling Efficient Spatio-Temporal GPU Sharing for network function virtualization

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IEEE TRANSACTIONS ON COMPUTERS 2023年第10期72卷 2963-2977页

作者： Zeng, Deze Zhu, Andong Gu, Lin Li, Peng Chen, Quan Guo, Minyi China Univ Geosci Sch Comp Sci Wuhan 430074 Peoples R China Nanjing Univ State Key Lab Novel Software Technol Nanjing 210023 Peoples R China Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Peoples R China Univ Aizu Sch Comp Sci & Engn Aizu Wakamatsu Japan Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai 200240 Peoples R China

By leveraging standard IT virtualization technology and Commercial-Off-The-Shelf (COTS) servers, network function virtualization (NFV) decouples network functions from proprietary hardware devices for flexible service provisioning. But the potential of NFV is significantly limited by its performance inefficiency. With the unparalleled advantages of multi-core parallelism and high memory bandwidth, Graphics Processing Units (GPUs) are regarded as a promising way to accelerate Virtualized network functions (VNF). However, the special architecture of GPU brings new challenges to task scheduling and resource allocation. To this end, we propose a GPU oriented spatio-temporal sharing framework for NFV called Gost, aiming for GPU based VNF performance promotion. The execution order and GPU resource allocation (i.e., the number of threads) are considered in task scheduling to minimize the end-to-end latency for VNF flows. First, we formulate the task scheduling problem into a nonlinear programming form, and then transform it into an equivalent Integer Linear Programming (ILP) form. The problem is proved as NP-hard. We customize the classical list scheduling algorithm and propose a List Scheduling based Spatio-Temporal GPU sharing strategy (LSSTG), whose achievable worst-case performance is also formally analyzed. We practically implement Gost prototype, based on which extensive experiments verify the high performance efficiency of LSSTG compared to state-of-the-art in terms of latency and throughput.

关键词： Graphics processing units Task analysis Kernel Scheduling Resource management Concurrent computing Computer architecture GPU acceleration network function virtualization spatio-temporal sharing task scheduling

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CoNFV: A Heterogeneous Platform for Scalable network function virtualization

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ACM TRANSACTIONS ON RECONFIGURABLE TECHNOLOGY AND SYSTEMS 2020年第1期14卷 1-29页

作者： Zhang, Xuzhi Shao, Xiaozhe Provelengios, George Dumpala, Naveen Kumar Gao, Lixin Tessier, Russell Univ Massachusetts Dept Elect & Comp Engn Amherst MA 01003 USA

network function virtualization (NFV) is a powerful networking approach that leverages computing resources to perform a time-varying set of network processing functions. Although microprocessors can be used for this purpose, their performance limitations and lack of specialization present implementation challenges. In this article, we describe a new heterogeneous hardware-software NFV platform called CoNFV that provides scalability and programmability while supporting significant hardware-level parallelism and reconfiguration. Our computing platform takes advantage of both field-programmable gate arrays (FPGAs) and microprocessors to implement numerous virtual network functions (VNF) that can be dynamically customized to specific network flow needs. The most distinctive feature of our system is the use of global network state to coordinate NFV operations. Traffic management and hardware reconfiguration functions are performed by a global coordinator that allows for the rapid sharing of network function states and continuous evaluation of network function needs. With the help of state sharing mechanism offered by the coordinator, customer-defined VNF instances can be easily migrated between heterogeneous middleboxes as the network environment changes. A resource allocation and scheduling algorithm dynamically assesses resource deployments as network flows and conditions are updated. We show that our deployment algorithm can successfully reallocate FPGA and microprocessor resources in a fraction of a second in response to changes in network flow capacity and network security threats including intrusion.

关键词： network function virtualization coordinator heterogeneous middle-boxes FPGA performance-aware VNF deployment

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Reconfiguration Aware Orchestration for network function virtualization With Time-Varied Workload in Virtualized Datacenters

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IEEE ACCESS 2021年 9卷 48413-48428页

作者： Padhy, Satyajit Chou, Jerry Natl Tsing Hua Univ Inst Informat Syst & Applicat Hsinchu 300044 Taiwan Natl Tsing Hua Univ Dept Comp Sci Hsinchu 300044 Taiwan

network function virtualization (NFV) is an emerging paradigm that has revolutionized the deployment and provisioning of telecommunication network services (NS). In NFV, a network service is implemented as a chain of network functions (NFs). NFs are virtualized and packaged into virtual network functions (VNF), so that they can be decoupled from the physical middleboxes and dynamically deployed on standard virtualization platforms in cloud or datacenters. Therefore, NFV has the potential to provide significant cost reductions in operating expenses (OPEX) and capital expenses (CAPEX) and increased agility for network service deployments. However, to build and manage a network function virtualization infrastructure (NFVI) is challenging. One of the key problems is to determine the mapping between underlying physical resources and VNFs in order to minimize energy consumption without violating service-level agreements (SLA). Many previous studies use embedding solutions to solve the problem by only considering the resource demand of NS and the resource capacity of physical network at a given time instance. But in practice, the resource demands of NS can vary over time, hence the embedding decision must be reconfigured accordingly. Many techniques can be used for reconfiguration, including resource scaling, instance migration and traffic re-direction. But each of these operation is associated with some costs, such as service interruptions, and additional resource or energy consumption. In this work, we investigate various reconfiguration strategies, formulate their costs by designing a model in the NFV placement problem, and propose Integer Linear Programming (ILP) and heuristic solutions, called REAP. In our evaluation, we observed 60% and 25% cost reduction for energy and reconfiguration costs, and we analyze the cost reduction from each of the reconfiguration methods to validate the design of our heuristic algorithm.

关键词： Delays Energy consumption virtualization network function virtualization Middleboxes Heuristic algorithms Bandwidth network function virtualization optimization scheduling resource management

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Research Challenges for network function virtualization - Re-Architecting Middlebox for High Performance and Efficient, Elastic and Resilient Platform to Create New Services

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IEICE TRANSACTIONS ON COMMUNICATIONS 2018年第1期E101B卷 96-122页

作者： Shiomoto, Kohei Tokyo City Univ Fac Knowledge Engn Tokyo 1588557 Japan

Today's enterprise, data-center, and internet-service-provider networks deploy different types of network devices, including switches, routers, and middleboxes such as network address translation and firewalls. These devices are vertically integrated monolithic systems. Software-defined networking (SDN) and network function virtualization (NFV) are promising technologies for dis-aggregating vertically integrated systems into components by using "softwarization". Software-defined networking separates the control plane from the data plane of switch and router, while NFV decouples high-layer service functions (SFs) or network functions (NFs) implemented in the data plane of a middlebox and enables the innovation of policy implementation by using SF chaining. Even though there have been several survey studies in this area, this area is continuing to grow rapidly. In this paper, we present a recent survey of this area. In particular, we survey research activities in the areas of re-architecting middleboxes, state management, high-performance platforms, service chaining, resource management, and trouble shooting. Efforts in these research areas will enable the development of future virtual-network-function platforms and innovation in service management while maintaining acceptable capital and operational expenditure.

关键词： network function virtualization software-defined networking service chain policy management resource management

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An Automated network Slicing at Edge with Software Defined networking and network function virtualization: A Federated Learning Approach

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WIRELESS PERSONAL COMMUNICATIONS 2023年第1期131卷 639-658页

作者： Rakkiannan, Thamilselvan Ekambaram, Gothai Palanisamy, Natesan Ramasamy, Rajalaxmi Rajammal Muthusamy, Suresh Loganathan, Ashok Kumar Panchal, Hitesh Thangaraj, Kokilavani Ravindaran, Ashokkumar Kongu Engn Coll Autonomous Dept Informat Technol Erode Tamil Nadu India Kongu Engn Coll Autonomous Dept Comp Sci & Engn Erode Tamil Nadu India Kongu Engn Coll Autonomous Dept Elect & Commun Engn Erode Tamil Nadu India PSG Coll Technol Dept Elect & Elect Engn Coimbatore Tamil Nadu India Govt Engn Coll Dept Mech Engn Patan Gujarat India Sri Krishna Coll Engn & Technol Autonomous Dept Elect & Elect Engn Coimbatore Tamil Nadu India Bannari Amman Inst Technol Autonomous Dept Elect & Elect Engn Erode Tamil Nadu India

network slicing allows heterogeneous applications can be launched across different domain using virtualized resources. The virtualized resources are created on the physical infrastructure. The orchestrator is essential for coordination of network slice management. The overhead in the slice orchestrator is reduced by distributed approach. The slice template act as a design specification template for the creation of network slices. This template can be predicted using federated learning, in which local models are trained with the generated data and global model is trained with local model parameters. Then the global parameters are updated in the local model for further learning. The federated model uses the Software Defined networking (SDN) capability to learn the local model data distribution and hence enhance global SDN federated controller prediction accuracy for network slices. This process can be automated with the help of slice template with the predicted pattern. The parameters of the slice template are directly proportional to the performance of the slice orchestrator and prediction of future slice demands. The edge devices with its local model communicate with the global SDN federated model to satisfy the requirement of dynamic network slicing. The request on-demand services can be provided as virtual network function using network function *** optimal resource allocation for the requested slice can be done with statistical modeling of observed traffic and autoscaling can be carried out. Experimental studies reveal that the proposed network slicing with federated approach minimal response time with maximal orchestrator scalability.

关键词： network slicing Federated learning Orchestrator Software defined networking network function virtualization

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Multimedia Content Delivery with network function virtualization: The Energy Perspective

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IEEE MULTIMEDIA 2017年第3期24卷 38-47页

作者： Fu, Silvery Liu, Jiangchuan Zhu, Wenwu Simon Fraser Univ Comp Sci Burnaby BC Canada Tsinghua Univ Comp Sci Dept Beijing Peoples R China

With the advent of network function virtualization, middleboxes are progressively embedded in off-the-shelf, general-purpose servers. Yet switching to NFV for multimedia content delivery can have high energy costs. Th... 详细信息

关键词： Multimedia Communication Middleboxes Streaming Media Servers network function virtualization Linux virtualization Green Computing Data Analysis Content Management Energy Efficiency network function virtualization Middleboxes Content Distribution networks Multimedia Communication Energy Efficiency Multimedia Green Computing networking virtualization Data Analysis

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Multi-Timescale Online Optimization of network function virtualization for Service Chaining

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2019年第12期18卷 2899-2912页

作者： Chen, Xiaojing Ni, Wei Chen, Tianyi Collings, Iain B. Wang, Xin Liu, Ren Ping Giannakis, Georgios B. Shanghai Univ Shanghai Inst Adv Commun & Data Sci Shanghai 200444 Peoples R China CSIRO Sydney NSW 2122 Australia Univ Minnesota Dept Elect & Comp Engn Digital Technol Ctr Minneapolis MN 55455 USA Macquarie Univ Sch Engn Sydney NSW 2109 Australia Fudan Univ Shanghai Inst Adv Commun & Data Sci Dept Commun Sci & Engn Key Lab Informat Sci Electromagnet Waves MoE 220 Handan Rd Shanghai 200433 Peoples R China Univ Technol Sydney Sch Elect & Data Engn Sydney NSW 2007 Australia

network function virtualization (NFV) can cost-efficiently provide network services by running different virtual network functions (VNFs) at different virtual machines (VMs) in a correct order. This can result in strong couplings between the decisions of the VMs on the placement and operations of VNFs. This paper presents a new fully decentralized online approach for optimal placement and operations of VNFs. Building on a new stochastic dual gradient method, our approach decouples the real-time decisions of VMs, asymptotically minimizes the time-average cost of NFV, and stabilizes the backlogs of network services with a cost-backlog tradeoff of [epsilon, 1/epsilon], for any epsilon > 0. Our approach can be relaxed into multiple timescales to have VNFs (re)placed at a larger timescale and hence alleviate service interruptions. While proved to preserve the asymptotic optimality, the larger timescale can slow down the optimal placement of VNFs. A learn-and-adapt strategy is further designed to speed the placement up with an improved tradeoff [epsilon, log(2)(epsilon)/root epsilon]. Numerical results show that the proposed method is able to reduce the time-average cost of NFV by 23 percent and reduce the queue length (or delay) by 74 percent, as compared to existing benchmarks.

关键词： network function virtualization virtual machine distributed optimization stochastic approximation

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