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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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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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network function virtualization: A Survey

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IEICE TRANSACTIONS ON COMMUNICATIONS 2017年第11期E100B卷 1978-1991页

作者： Veeraraghavan, Malathi Sato, Takehiro Buchanan, Molly Rahimi, Reza Okamoto, Satoru Yamanaka, Naoaki Univ Virginia 351 McCormick Rd Charlottesville VA 22904 USA Keio Univ Yokohama Kanagawa 2238522 Japan

The objectives of this survey are to provide an in-depth coverage of a few selected research papers that have made significant contributions to the development of network function virtualization (NFV), and to provide readers insights into the key advantages and disadvantages of NFV and Software Defined networks (SDN) when compared to traditional networks. The research papers covered are classified into four categories: NFV Infrastructure (NFVI), network functions (NFs), Management And network Orchestration (MANO), and service chaining. The NFVI papers describe "framework" software that implement common functions, such as dynamic scaling and load balancing, required by NF developers. Papers on NFs are classified as offering solutions for software switches or middleboxes. MANO papers covered in this survey are primarily on resource allocation (virtual network embedding), which is an orchestrator function. Finally, service chaining papers that offer examples and extensions are reviewed. Our conclusions are that with the current level of investment in NFV from cloud and Internet service providers, the promised cost savings are likely to be realized, though many challenges remain.

关键词： network function virtualization Software Defined networks Software switches middleboxes orchestrators

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End to end delay aware service function chain scheduling in network function virtualization enabled networks

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PEER-TO-PEER networkING AND APPLICATIONS 2024年第6期17卷 3883-3904页

作者： Dubba, Sudha Killi, Balaprakasa Rao Natl Inst Technol Dept Comp Sci & Engn Warangal 506003 Telangana India

network function virtualization is a key enabling technology for the customization of network services in next-generation networks to support diverse applications. Most enterprise and network services contain specific network functions that are stitched together in a predefined sequence to form a service function chain. The deployment and scheduling of a service function chain onto the substrate network play a vital role in deciding the efficiency of resource utilization and the performance of network management. For a delay-sensitive network service request traversing a service function chain, the end-to-end packet delay is a crucial parameter that indicates the deployment performance. Transmission, propagation, processing, edge queueing, and virtualization delays all impact the order in which virtual network functions execute. Service level agreement violations and incorrect schedules are produced when the controller does not take edge queueing and virtualization delays into account. In this work, we propose a service function chain scheduling problem for the optimization of the end-to-end delay while considering transmission, propagation, queueing, virtualization, and processing delays. Then, we propose a scheduling approach based on the earliest finish times of the physical machines to minimize the end-to-end delay of the service function chain. The performance of the proposed service function chain scheduling approach using the earliest finish time is evaluated in terms of end-to-end delay, service level agreement violation ratio, resource utilization, and acceptance ratio. We compare our proposed algorithm with four existing approaches from the literature. Simulation results show that our proposed approach outperforms existing approaches in terms of end-to-end delay, service level agreement violation ratio, resource utilization, and acceptance ratio.

关键词： network function virtualization Service function chain scheduling End-to-end delay Service level agreement violation ratio

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Transport network function virtualization

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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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Data-Plane-Assisted State Replication With network function virtualization

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IEEE SYSTEMS JOURNAL 2022年第2期16卷 2934-2945页

作者： Lotfimahyari, Iman Sviridov, German Giaccone, Paolo Bianco, Andrea Politecn Torino Dipartimento Elettron & Telecomunicaz I-10129 Turin Italy

Modern 5G networks are capable of providing ultralow-latency and highly scalable network services by employing modern networking paradigms, such as software-defined networking (SDN) and network function virtualization. The latter enables performance-critical network applications to be run in a distributed fashion directly inside the infrastructure. Being distributed, those applications rely on sophisticated state replication algorithms to synchronize states among each other. Nevertheless, current implementations of such algorithms do not fully exploit the potential of the modern infrastructures, thus leading to suboptimal performance. In this article, we propose STARE, a novel state replication system tailored for 5G networks. At its core, STARE exploits stateful SDN to offload replication-related processes to the data plane, ultimately leading to reduced communication delays and processing overhead for virtual network functions. We provide a detailed description of the STARE architecture alongside a publicly-available P4-based implementation. Furthermore, our evaluation shows that STARE is capable of scaling to big networks while introducing low overhead in the network.

关键词： Protocols network function virtualization Partitioning algorithms 5G mobile communication Wireless fidelity Scalability Real-time systems 5G network function virtualization (NFV) programmable data planes publish– subscribe model state sharing

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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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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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Service Deployment With Priority Queueing for Traffic Processing and Transmission in network function virtualization

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IEEE TRANSACTIONS ON network AND SERVICE MANAGEMENT 2023年第4期20卷 4861-4874页

作者： He, Fujun Oki, Eiji Kyoto Univ Grad Sch Informat Kyoto 6068501 Japan Huawei Technol Co Ltd Shenzhen 518063 Peoples R China

network function virtualization enables service providers to flexibly deploy network services. The existing works mainly focus on function placement and capacity allocation without exploring traffic scheduling for service deployment, by adopting a first-in-first-out policy. It introduces inefficiency considering that different services vary in the delay requirements. This paper proposes a service deployment model with priority queuing for both traffic processing and transmission to minimize the deployment cost with satisfying the service delay constraints. We analyze the problem including proving its NP-hardness and the convexity of a subproblem. Based on the analysis, we develop a reinforcement learning-based approach to address the problem in a decomposition manner with a polynomial-time complexity in each episode. Several specific designs are introduced to fit the learning-based approach to the considered deployment problem with priority queueing. The numerical results show that the introduced approach achieves an objective value comparable to the optimal one obtained by brute force search with a computation time 10(3) times shorter. Compared to a conventional model with the first-in-first-out policy, the proposed model reduces the deployment cost by adopting a more flexible queueing policy.

关键词： network function virtualization service deployment priority queueing reinforcement learning

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Efficient algorithms to minimize the end-to-end latency of edge network function virtualization

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JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING 2020年第10期11卷 3963-3974页

作者： Ghai, Karanbir Singh Choudhury, Salimur Yassine, Abdulsalam Lakehead Univ Dept Comp Sci Thunder Bay ON Canada Lakehead Univ Dept Software Engn Thunder Bay ON Canada

In future wireless networks, network function virtualization will lay the foundation for establishing a new dynamic resource management framework to efficiently utilize network resources. The main problem discussed in this paper is the minimization of total latency for an edge network and how to solve it efficiently. A model of users, virtual network functions and hosting devices has been taken, and is used to find the minimum latency using integer linear programming. The problem is NP-hard and takes exponential time to return the optimal solution. We apply the stable matching based algorithm to solve the problem in polynomial time and then utilize local search to improve its efficiency further. From extensive performance evaluation, it is found that our proposed algorithm is very close to the optimal scheme in terms of latency and better in terms of time complexity.

关键词： network function virtualization Hosting device Latency Stable matching Local search

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