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IEEE Conference on Standards for Communications and networking (IEEE CSCN)

作者： Zalokostas-Diplas, Vasileios Makris, Nikos Passas, Virgilios Korakis, Thanasis Univ Thessaly Dept Elect & Comp Engn Volos Greece Ctr Res & Technol Hellas CERTH Maroussi Greece

ISBN: (纸本)9781665476218

network functions virtualization (NFV) is a key aspect deeply integrated in the latest 5G networks, allowing for the provisioning of elastic resources that adapt in a flexible manner based on the overall network demand. The adoption of NFV architectures is empowered through the evolution of cloud-native and hypervisor tools to support service monitoring, and orchestrate the appropriate decisions for provisioning the scale of the network. Such decisions may directly impact the overall quality of service and experience for users, as well as the energy consumption that the resources use. To this aim, machine learning (ML) - driven optimization for these decisions, relying on inferring the values of future monitored metrics, can assist in deciding proactively on the network scale. In this work, we employ three different candidate solutions (statistical, tree- and CNN-based) for determining the scale of network functions deployed within a cluster of resources, subject to the user demand. We compare and evaluate the different schemes in a real testbed environment, and discuss the benefits of ML-driven optimizations against existing state-of-the-art approaches.

关键词： network function virtualization

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Research on Fault Management System based on Artificial Intelligence in Data network

Research on Fault Management System based on Artificial Inte...

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2023 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2023

作者： Dong, Yunzhou Wang, Xinyu Fu, Fangyou Lin, Zhengdong Yin, Chaona Liao, Yingkun Lin, Peng Hainan Power Grid Communication Branch HaiKou China University at Buffalo The State University of New York New York United States Beijing VectInfo Technologies Co. Ltd. Beijing China

ISBN: (纸本)9798350321524

SDN, NFV and other technologies increase the complexity of data network systems, resulting in an increase in the probability of network failures and the difficulty of maintenance. In order to design a more practical fault management framework and mechanism, the data network environment is analyzed first. Based on the characteristics of data network environment and network elements, a fault management architecture based on artificial intelligence is proposed. The architecture includes device layer, data acquisition layer, data analysis layer and data management layer. In order to improve the application value and convenience of the fault management architecture, the elastic strategy, self-healing strategy and work order distribution mechanism of the data management layer are designed in detail. In the performance analysis, from the implementation feasibility and performance aspects, it is verified that the fault management mechanism proposed in this paper has good application value. © 2023 IEEE.

关键词： network function virtualization

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Efficient Decomposition-Based Methods for Optimal VNF Placement and Chaining 24

Efficient Decomposition-Based Methods for Optimal VNF Placem...

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24th Asia-Pacific network Operations and Management Symposium, APNOMS 2023

作者： Ikhelef, Issam Abdeldjalil Warwicker, John Alasdair Rebennack, Steffen Saidi, Mohand Yazid Chen, Ken L2TI - Institut Galilée Université Sorbonne Paris Nord Villetaneuse France Institute of Operations Research - Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9788995004395

The concepts of network function virtualization (NFV) and software-defined networks (SDNs) are emerging as core technologies to satisfy the growing number of user demands in 5G wireless networks and beyond. NFV and SDNs offer network providers the ability to deliver scalable, lower-cost services free from the constraints of hardware components. The virtual network function placement and chaining (VNF-PC) problem is considered in this paper. VNF-PC involves placing virtual network functions (VNFs) optimally in a distributed NFV infrastructure (NFV-I), efficiently allocating network resources to these VNFs to satisfy users demands and directing the network flow through the VNFs. Current solutions to this problem are time-consuming, cannot handle real-time queries, or use heuristic methods to find approximate solutions. To this end, we propose an efficient exact solution method for the VNF-PC problem through decomposition. We show how decomposing the problem can allow us to assess the viability of incumbent solutions and use this information to provide effective cuts. We further augment this exact solution approach by using a greedy branching heuristic to explore more fruitful areas of the search space. Experimental results show the potential of this combined approach. Copyright 2023 KICS.

关键词： network function virtualization

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Reliability-assured service function chain migration strategy in edge networks using deep reinforcement learning

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JOURNAL OF network AND COMPUTER APPLICATIONS 2024年 231卷

作者： Li, Yilin Zhang, Peiying Kumar, Neeraj Guizani, Mohsen Wang, Jian Kostromitin, Konstantin Igorevich Wang, Yi Tan, Lizhuang China Univ Petr East China Qingdao Inst Software Coll Comp Sci & Technol Qingdao 266580 Peoples R China Qilu Univ Technol Key Lab Comp Power Network & Informat Secur Natl Supercomp Ctr Jinan Minist EducShandong Comp Sci CtrShandong Acad Sc Jinan 250013 Peoples R China Thapar Univ Dept Comp Sci & Engn Patiala 147004 India Mohamed Bin Zayed Univ Artificial Intelligence Machine Learning Dept Abu Dhabi 999041 U Arab Emirates China Univ Petr East China Coll Sci Qingdao 266580 Peoples R China South Ural State Univ Dept Phys Nanoscale Syst Chelyabinsk 454080 Russia Southern Univ Sci & Technol Inst Future Networks Shenzhen 518055 Peoples R China Peng Cheng Lab Shenzhen 518038 Peoples R China Shandong Fundamental Res Ctr Comp Sci Shandong Prov Key Lab Comp Networks Jinan 250013 Peoples R China

With the widespread adoption of edge computing and the rollout of 5G technology, the edge network is experiencing rapid growth. Edge computing enables the execution of certain computational tasks on edge devices, fostering more efficient resource utilization. However, the reliability of the edge network is constrained by its network connections. network instability can significantly compromise service quality. An effective service function chain (SFC) migration algorithm is essential to optimize resource utilization, enhance service quality. This paper begins by analyzing the current research landscape of edge networks and SFC migration algorithms. Subsequently, the challenges associated with edge network and SFC migration are formally articulated, leading to the proposal of a SFC migration algorithm based on deep reinforcement learning (DRL) with a focus on reliability assurance (RA-SFCM). The algorithm leverages multi-agent deep reinforcement learning to dynamically perceive changes in the edge network environment. It introduces an advantage function to evaluate the performance of each agent relative to the average level and incorporates a central attention mechanism with multiple attention heads to better capture the interdependencies and relationships among different agents. Additionally, this paper innovatively defines and quantifies the reliability of the migration process. By introducing a reliability penalty mechanism based on the migration target nodes and link capacity, it enhances the reliability of the migration schemes. The experimental results conclusively demonstrate the remarkable advantages of the RA-SFCM algorithm in terms of real-time performance, resource utilization efficiency, and reliability. Compared to algorithms such as Sa-VNFM, ROVM, and DLTSAC, RA-SFCM exhibits superior performance. For RA-SFCM, the optimized deployment migration strategy enhances realtime performance, precise resource management improves utilization efficiency, and advan

关键词： Edge network network function virtualization Service function chain migration Reliability

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Toward Flexible Auditing for In-network functionality 3

Toward Flexible Auditing for In-Network Functionality

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ACM International CoNEXT Student Workshop (CoNEXT-SW) Part of 18th International Conference on Emerging networking Experiments and Technologies (CoNEXT)

作者： Sun, Shuwen Choffnes, David Northeastern Univ Boston MA 02115 USA

ISBN: (纸本)9781450399371

networks today increasingly support in-network functionality via network function virtualization (NFV) or similar technologies. Such approaches enable a wide range of functionality to be deployed on behalf of end systems, such as offloading Tor services [5], enforcing network usage policies on encrypted traffic [6], or new functionality in 5G [3]. An important open problem with such approaches is auditing. Namely, such services rely on third-party network providers to faithfully deploy and run their functionality as intended, but often have little to no insight as to whether providers do so. To address this problem, prior work provides point solutions such as verifiable routing with per-packet overhead [1], or audits of security practices [4];however, these approaches are not flexible - -they are limited to auditing a small set of functionality and do not allow trade-offs between auditing coverage and overhead. In this paper, we propose NFAudit, which allows auditing of deployed NFs with a flexible approach where a wide range of important properties can be audited with configurable, low overhead. Our key insight is that the design of simple, composable, and flexible auditing primitives, combined with limited trust (in the form of secure enclaves) can permit a wide range of auditing functionality and configurable - -and often low - -cost. © 2022 Owner/Author.

关键词： network function virtualization

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Service Deployment on Shared Virtual network functions with Flow Partition

Service Deployment on Shared Virtual Network Functions with ...

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IEEE International Conference on Communications (ICC)

作者： Zhang, Jingxiong He, Fujun Oki, Eiji Kyoto Univ Grad Sch Informat Kyoto Japan

ISBN: (数字)9781538683477

ISBN: (纸本)9781538683477

network operators can operate services in a flexible way with virtual network functions thanks to the network function virtualization technology. Flow partition allows aggregated traffic to be split into multiple parts, which increases the flexibility. This paper proposes a service deployment model with flow partition to minimize the total deployment cost with meeting service time delay requirements. A virtual network function of a service is allowed to have several instances, each of which hosts a part of flows and can be shared among different services, to reduce the initial and proportional cost. We provide the mathematical formulation for the proposed model. A heuristic algorithm is introduced to solve the original problem in practical time by decomposing it into several steps;each step handles a convex problem. The numerical results reveal that the proposed model saves the total deployment cost compared to the conventional one. It improves the maximum admissible traffic scale by 23% in average in our examined cases.

关键词： network function virtualization service deployment flow partition queueing theory

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Virtual network function Placement Model Considering Both Service Delay and Availability 23

Virtual Network Function Placement Model Considering Both Se...

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23rd Asia-Pacific network Operations and Management Symposium (APNOMS)

作者： Horimoto, Shinya Oki, Eiji Kyoto Univ Kyoto Japan

ISBN: (数字)9784885523397

ISBN: (纸本)9784885523397

This paper proposes a virtual network function (VNF) placement model considering both availability and probabilistic protection for service delay to minimize the service deployment cost. Both availability and service delay are key requirements of services;a service provider handles the VNF placement problem with the goal of minimizing the service deployment cost while meeting these and other requirements. The previous works do not consider the delay of each route which the service can take when considering both availability and delay in the VNF placement problem;only the maximum delay was considered. We introduce probabilistic protection for service delay to minimize the service deployment cost with availability. The proposed model considers that the probability that the service delay, which consists of networking delay between hosts and processing delay in each VNF, exceeds its threshold is constrained within a given value;it also considers that the availability is constrained within a given value. We develop a two-stage heuristic algorithm to solve the VNF placement problem;it decides primary VNF placement by solving mixed-integer second-order cone programming in the first stage and backup VNF placement in the second stage. We observe that the proposed model reduces the service deployment cost compared to a baseline by up to 10%, and that it obtains a feasible solution while the baseline does not in some examined situations.

关键词： network function virtualization virtual network function placement service delay availability

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Constrained routing in multi-partite graph to solve VNF placement and chaining problem

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JOURNAL OF network AND COMPUTER APPLICATIONS 2024年 230卷

作者： Saidi, Mohand Yazid Ikhelef, Issam Abdeldjalil Li, Shuopeng Chen, Ken Univ Sorbonne Paris Nord L2TI Inst Galilee Villetaneuse France Beijing Univ Technol Fac Informat Technol Beijing Peoples R China

network functions virtualization (NFV) and Software-Defined networks (SDN) empower IT professionals and service providers to strategically deploy Virtual network functions (VNFs), resulting in enhanced services and security while minimizing costs. network services are dynamically provided through the deployment of Service function Chains (SFCs), which involve selecting and interconnecting physical or virtual servers hosting VNFs. In this paper, we address the online VNF placement and chaining (VNF-PC) problem, aiming to optimize the overall cost while satisfying the resource constraints. We begin by proving the NP-completeness of finding feasible solutions for both fixed-size NFV infrastructures and constant-size SFCs. Subsequently, we formulate the VNF-PC problem using Integer Linear Programming (ILP), which is adept at handling and solving small-scale instances of the problem. However, the efficiency of ILP hinges on the quality and quantity of precomputed paths, a factor that escalates rapidly with the expansion of NFV infrastructure size. To tackle scalability, we initially suggest resource homogenization using a novel multi-partite graph, followed by the introduction of the Constrained Shortest Path-based Heuristic in multi-Partite Graph (CSPH-PG) to solve the VNF-PC problem in polynomial time. Our heuristic focuses on promising solution areas by restricting the exploration to the K shortest paths that meet the constraints at each node, with K acting as a fixed parameter of our heuristic. Extensive simulations demonstrate that our heuristic rapidly converges towards optimal solutions, even with small values of the parameter K .

关键词： Virtual network function network function virtualization Software defined network Service function chain Optimization Multi-constrained routing

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Edge network softwarization and intelligence: Challenges and opportunities

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COMPUTER networkS 2024年 255卷

作者： Troia, Sebastian Savi, Marco Grasso, Christian Slyne, Frank Ruan, Lihua Seufert, Michael Politecn Milan Milan Italy Univ Milano Bicocca Milan Italy Univ Catania Catania Italy Trinity Coll Dublin Dublin Ireland Peng Cheng Lab Shenzhen Peoples R China Univ Augsburg Augsburg Germany

This Editorial provides an overview of the Special Issue "Edge network Softwarization and Intelligence: Challenges and Opportunities (EdgeNetSoft)", published in Elsevier's Computer networks in 2024. We begin by outlining the motivation and context that highlight the significance of this topic, followed by a concise classification and discussion of the articles included in this issue. Finally, we propose potential directions for future research, offering insights into the evolving landscape of edge network softwarization and intelligence.

关键词： Edge networks Software-defined networking Software-defined wide area network network softwarization network function virtualization 5G/6G Artificial intelligence Machine learning

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The Way to Support Virtual Resource Mapping Within Dynamic network Infrastructure

The Way to Support Virtual Resource Mapping Within Dynamic N...

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2024 International Conference on Information Science and Communications Technologies, ICISCT 2024

作者： Amirsaidov, U.B. Usmanova, N.B. Abdujalilov, J.A. Tashkent University of Information Technologies named after Mukhammad al-Khwarizmi (TUIT) Department of Data Communication Networks and Systems Uzbekistan

ISBN: (纸本)9798331527921

network virtualization therefore refers to the integration of physical hardware and software network resources and network functionality into one software control entity - a virtual network. Virtual networks enable several different kinds of heterogenous Logical networks to share the same Physical network. The main work in incarnating virtualization is to provision the physical network resources to a given virtual network by mapping the virtual resources to the physical equipment dynamically in order to leverage the available equipments. Opinions derived from experimental as well as real life scenario reveal that mechanisms of virtualization will be the key enabler of end to end Quality of Service assurance in the network architecture. This paper considers how to arrange the virtual services approaching the task of virtual resource mapping in network environment, with possibility to focus on the network elements performing the network functions and interfacing with prospective networking solutions. © 2024 IEEE.

关键词： network function virtualization Software defined networking Virtual computing nodes (servers) Virtual nodes Virtual routers Virtual storage devices

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