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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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Minimizing Delay in network function virtualization with Shared Pipelines

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2017年第1期28卷 156-169页

作者： Rottenstreich, Ori Keslassy, Isaac Revah, Yoram Kadosh, Aviran Princeton Univ Dept Comp Sci Princeton NJ 08544 USA Technion Dept Elect Engn Haifa Israel Marvell Israel Yokneam Israel

Pipelines are widely used to increase throughput in multi-core chips by parallelizing packet processing while relying on virtualization. Typically, each packet type is served by a dedicated pipeline with several cores, each implementing a network service. However, with the increase in the number of packet types and their number of required services, there are not enough cores for pipelines. In this paper, we study pipeline sharing, such that a single pipeline can be used to serve several packet types. Pipeline sharing decreases the needed total number of cores, but typically increases pipeline lengths and therefore packet delays. We consider two novel optimization problems of allocating cores between different packet types such that the average or the worst-case delay is minimized. We study the two problems and suggest optimal algorithms that apply under different assumptions on the input. We also present greedy algorithms for the general case. Last, we examine our solutions on synthetic examples as well as on real-life applications and demonstrate that they often achieve close-to-optimal delays.

关键词： network function virtualization multicore optimization network processors

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Routing Algorithms for network function virtualization Enabled Multicast Topology on SDN

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IEEE TRANSACTIONS ON network AND SERVICE MANAGEMENT 2015年第4期12卷 580-594页

作者： Zhang, Sai Qian Zhang, Qi Bannazadeh, Hadi Leon-Garcia, Alberto Univ Toronto Dept Elect & Comp Engn Toronto ON MSS 3G4 Canada

Many multicast services such as live multimedia distribution and real-time event monitoring require multicast mechanisms that involve network functions (e.g., firewall and video transcoding). network function virtualization (NFV) is a concept that proposes using virtualization to implement network functions on infrastructure building block (such as high volume servers and virtual machines), where software provides the functionality of existing purpose-built network equipment. We present an approach for building the multicast mechanism whereby multicast flows are processed by NFV before reaching their end users. We propose a routing algorithm and a method for building an appropriate multicast topology.

关键词： network function virtualization software defined networking traffic engineering

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Evolving Security for 6G: Integrating Software-Defined networking and network function virtualization into Next-Generation Architectures

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2024年第6期15卷 909-914页

作者： Jaadouni, Hatim Chaoui, Habiba Saadi, Chaimae Natl Sch Appl Sci Kenitra Sci & Engn Lab Kenitra Morocco EST Sale Lab Syst Anal Informat Proc & Ind Management LAST Sale Morocco

As technology continues to advance, the emergence of 6G networks is imminent, promising unprecedented levels of connectivity and innovation. A critical aspect of designing the security architecture for 6G networks revolves around the utilization of Software-Defined networking (SDN) and network function virtualization (NFV) technologies. By harnessing the capabilities of SDN and NFV, the security infrastructure of 6G networks stands to gain significant advantages in terms of flexibility, scalability, and agility. SDN facilitates the decoupling of the network control plane from the data plane, enabling centralized management and control of network resources. This article examines the synergistic relationship between SDN and NFV in enhancing the resilience and adaptability of 6G security architectures, offering insights into key challenges, emerging trends, and future directions in securing the next generation of wireless networks.

关键词： 6G network network function virtualization software defined network security architecture

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Adaptive service function selection for network function virtualization networking

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2019年 91卷 108-123页

作者： Ma, Yi-Wei Chen, Jiann-Liang Jhou, Jia-Yi Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei Taiwan Shanghai Maritime Univ China Inst FTZ Supply Chain Shanghai Peoples R China

In multiple Service Nodes (SNs) in a network function virtualization (NFV) environment, numerous network functions are carried out. This study concerns the selection of Service function Instances (SFIs) that are integrated into a Service function Path (SFP) in resource-constrained networks with various functional requirements. Imbalanced loads in the network system are prevented and a service chain with a high Service Level Agreement (SLA) is developed. An NFV-based Service function Chain (SFC) integration architecture is designed and an SFP selection mechanism is developed to provide a flexible service chain that satisfies service requests. Two cases are discussed to analyze the effectiveness of the mechanism. The proposed SFP selection mechanism improves the resource utilization of SFIs, prevents the overloading of SFIs, increases the number of service chains that can be serviced by the system, and reduces the packet loss rate. The proposed selection mechanism is compared with without selection mechanism to verify its performance. In case 1, only the load of the SFIs is considered. An SFC controller with the proposed SFP selection mechanism improves resource utilization by 21.32% and reduces the standard deviation of instantaneous loads by 30.02%. In case 2, the acceptable price of instances of service function is considered. The case 2 improves resource utilization by 10.31%, and the standard deviation of the instantaneous load is reduced by 18.73%. An analysis of the rejection rate indicates that the proposed mechanism improves the number of service chains that can be serviced by the system and reduces the mean packet loss rate by 1.91%. (C) 2018 Elsevier B.V. All rights reserved.

关键词： network function virtualization Service function chaining Service function path Load balancing

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Implementing Internet of Things Service Platforms with network function virtualization Serverless Technologies

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FUTURE INTERNET 2024年第3期16卷 91页

作者： Femminella, Mauro Reali, Gianluca Univ Perugia Dept Engn via G Duranti 93 I-06125 Perugia Italy Consorzio Nazl Interuniv Telecomunicaz CNIT I-43124 Parma Italy

The need for adaptivity and scalability in telecommunication systems has led to the introduction of a software-based approach to networking, in which network functions are virtualized and implemented in software modules, based on network function virtualization (NFV) technologies. The growing demand for low latency, efficiency, flexibility and security has placed some limitations on the adoption of these technologies, due to some problems of traditional virtualization solutions. However, the introduction of lightweight virtualization approaches is paving the way for new and better infrastructures for implementing network functions. This article discusses these new virtualization solutions and shows a proposal, based on serverless computing, that uses them to implement container-based virtualized network functions for the delivery of advanced Internet of Things (IoT) services. It includes open source software components to implement both the virtualization layer, implemented through Firecracker, and the runtime environment, based on Kata containers. A set of experiments shows that the proposed approach is fast, in order to boost new network functions, and more efficient than some baseline solutions, with minimal resource footprint. Therefore, it is an excellent candidate to implement NFV functions in the edge deployment of serverless services for the IoT.

关键词： Internet of Things micro virtual machines network function virtualization serverless computing performance evaluation

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Lagrangian Relaxation Based Parallelized Quantum Annealing and Its Application in network function virtualization

IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY

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IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY 2024年 5卷 4260-4274页

作者： Xuan, Wenlu Zhao, Zhongqi Fan, Lei Han, Zhu Univ Houston Dept Elect & Comp Engn Houston TX 77204 USA Univ Houston Dept Engn Technol Houston TX 77204 USA Kyung Hee Univ Dept Comp Sci & Engn Seoul 446701 South Korea

Quantum computing is commonly considered one highly efficient computing method with the potential to revolutionize computation technology and solve problems that are currently unsolvable. However, due to the limitation of hardware equipment and an immature experimental base, quantum technology is still in its early stages and is far from achieving the expected performance, especially in solving large-scale complex problems. To break through these barriers, we propose a parallelized quantum annealing algorithm based on Lagrangian relaxation. The proposed algorithm divides the large-scale problem into several small problems and then employs multiple quantum computers to solve them. Our proposed approach overcomes the limited number of qubits and allows quantum computing to solve largescale optimization problems. Additionally, we incorporate a local search method to ensure this Lagrangian relaxation based quantum algorithm achieves an optimal solution. We use the proposed parallelized quantum annealing algorithm to solve optimal scheduling problems in network function virtualization networks. The problem is expressed in a linear optimization model that is NP-hard. Our proposed algorithm presents excellent time performance in solving this virtualized network functions scheduling problem, compared with the Lagrangian relaxation based classical algorithm.

关键词： Quantum annealing Annealing Quantum computing Quantum mechanics Simulated annealing Computational modeling Qubit Lagrangian relaxation quantum algorithm network function virtualization quantum computing virtualized network functions scheduling problem optimization problem tabu search algorithm

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Machine Learning for Dynamic Resource Allocation in network function virtualization 6

Machine Learning for Dynamic Resource Allocation in Network ...

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6th IEEE International Conference on network Softwarization (NetSoft) - Bridging the Gap Between AI and network Softwarization

作者： Schneider, Stefan Satheeschandran, Narayanan Puthenpurayil Peuster, Manuel Karl, Holger Paderborn Univ Paderborn Germany Amrita Sch Engn Amritapuri India

ISBN: (纸本)9781728156842

network function virtualization (NFV) proposes to replace physical middleboxes with more flexible virtual network functions (VNFs). To dynamically adjust to ever-changing traffic demands, VNFs have to be instantiated and their allocated resources have to be adjusted on demand. Deciding the amount of allocated resources is non-trivial. Existing optimization approaches often assume fixed resource requirements for each VNF instance. However, this can easily lead to either waste of resources or bad service quality if too many or too few resources are allocated. To solve this problem, we train machine learning models on real VNF data, containing measurements of performance and resource requirements. For each VNF, the trained models can then accurately predict the required resources to handle a certain traffic load. We integrate these machine learning models into an algorithm for joint VNF scaling and placement and evaluate their impact on resulting VNF placements. Our evaluation based on real-world data shows that using suitable machine learning models effectively avoids over- and under-allocation of resources, leading to up to 12 times lower resource consumption and better service quality with up to 4.5 times lower total delay than using standard fixed resource allocation.

关键词： network function virtualization

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network function virtualization and Service function Chaining Frameworks: A Comprehensive Review of Requirements, Objectives, Implementations, and Open Research Challenges

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FUTURE INTERNET 2022年第2期14卷 59页

作者： Adoga, Haruna Umar Pezaros, Dimitrios P. Univ Glasgow Sch Comp Sci Glasgow G12 8QQ Lanark Scotland

network slicing has become a fundamental property for next-generation networks, especially because an inherent part of 5G standardisation is the ability for service providers to migrate some or all of their network services to a virtual network infrastructure, thereby reducing both capital and operational costs. With network function virtualisation (NFV), network functions (NFs) such as firewalls, traffic load balancers, content filters, and intrusion detection systems (IDS) are either instantiated on virtual machines (VMs) or lightweight containers, often chained together to create a service function chain (SFC). In this work, we review the state-of-the-art NFV and SFC implementation frameworks and present a taxonomy of the current proposals. Our taxonomy comprises three major categories based on the primary objectives of each of the surveyed frameworks: (1) resource allocation and service orchestration, (2) performance tuning, and (3) resilience and fault recovery. We also identify some key open research challenges that require further exploration by the research community to achieve scalable, resilient, and high-performance NFV/SFC deployments in next-generation networks.

关键词： network function virtualization service function chaining software defined networking next-generation networks SFC frameworks

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Delay-Aware Scheduling and Resource Optimization With network function virtualization

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IEEE TRANSACTIONS ON COMMUNICATIONS 2016年第9期64卷 3746-3758页

作者： Qu, Long Assi, Chadi Shaban, Khaled Qatar Univ Dept Comp Sci & Engn Doha 2713 Qatar Concordia Univ Montreal PQ H3G 1M8 Canada

To accelerate the implementation of network functions/middle boxes and reduce the deployment cost, recently, the concept of network function virtualization (NFV) has emerged and become a topic of much interest attracting the attention of researchers from both industry and academia. Unlike the traditional implementation of network functions, a softwareoriented approach for virtual network functions (VNFs) creates more flexible and dynamic network services to meet a more diversified demand. Software-oriented network functions bring along a series of research challenges, such as VNF management and orchestration, service chaining, VNF scheduling for low latency and efficient virtual network resource allocation with NFV infrastructure, among others. In this paper, we study the VNF scheduling problem and the corresponding resource optimization solutions. Here, the VNF scheduling problem is defined as a series of scheduling decisions for network services on network functions and activating the various VNFs to process the arriving traffic. We consider VNF transmission and processing delays and formulate the joint problem of VNF scheduling and traffic steering as a mixed integer linear program. Our objective is to minimize the makespan/latency of the overall VNFs' schedule. Reducing the scheduling latency enables cloud operators to service (and admit) more customers, and cater to services with stringent delay requirements, thereby increasing operators' revenues. Owing to the complexity of the problem, we develop a genetic algorithm-based method for solving the problem efficiently. Finally, the effectiveness of our heuristic algorithm is verified through numerical evaluation. We show that dynamically adjusting the bandwidths on virtual links connecting virtual machines, hosting the network functions, reduces the schedule makespan by 15%-20% in the simulated scenarios.

关键词： network function virtualization scheduling bandwidth allocation genetic algorithm

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