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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Xu, Xinmian Dou, Haie Chen, Mingkai Wang, Lei Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing210003 China

ISBN: (纸本)9798350345384

In recent years, there has been significant attention and development in the Tactile Internet (TI) as a new type of network that supports typical applications such as remote healthcare and virtual reality. However, the demand for ultra-low latency and the inflexibility of traditional network architecture have presented serious challenges. In this paper, we propose a utility function for TI based on 5G network function virtualization (NFV) technology to evaluate network performance. The utility function considers the transmission of haptic and video data flows, as well as their latency and cost. We then formulate a network optimization problem with the utility function as the objective, strictly constraining latency and cost. To address this problem, we design two algorithms: the VNF deployment and routing of haptic and video flows (DRHV) algorithm tackles the VNF deployment and path selection issue, while the deep deterministic policy gradient(DDPG)-based traffic scheduling (DTS) algorithm allocates traffic resources and saves costs. Simulation results demonstrate that our algorithms achieve excellent optimization performance under the given constraints, and parameter changes align with the expected relationships and trends. © 2023 IEEE.

关键词： network function virtualization

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Parallel Deployment of Service function Chains Based on network State Prediction 2

Parallel Deployment of Service Function Chains Based on Netw...

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2nd International Conference on Signal Processing, Computer networks and Communications, SPCNC 2023

作者： Song, Yu Peng, Rumeng Feng, Xu Zhang, Kunli Zhuang, Lei He, Mengyang The School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou China The School of Cyber Science and Engineering Zhengzhou University Zhengzhou China

ISBN: (纸本)9798400716430

network function virtualization (NFV) transforms network functions into virtualized instances to enhance the flexibility, reliability, and scalability of the network, reduce network deployment and maintenance costs, and improve service quality and flexibility. Service function Chains (SFC) has also become a popular form of network services with the development of NFV, allowing network traffic to pass through a series of virtualized network functions in a specific order. The deployment of SFC has become a research hotspot in NFV. Because the deployment of SFC requests depends on the current network state and the network state changes after deployment, there is a certain topological dependency among the deployments of multiple requests. Therefore, many recent research works have adopted a serial approach to deploy multiple requests one after another, which requires more response time to handle burst traffic. This paper proposes a parallel deployment algorithm based on the Seq2Seq model for network state prediction. This way, the deployment of each request only depends on the predicted network state by the model, breaking the topological dependency among deployments of multiple requests, and enabling the simultaneous deployment of multiple requests. We trained the Seq2Seq prediction model on networks of various scales and modified the existing serial algorithm to a state prediction-based parallel algorithm. Experimental results demonstrate that compared to the serial algorithm, the proposed algorithm reduces the average response time for deploying burst traffic by 2.52-3.94 times, while also exhibiting good robustness in physical networks of different scales. © 2023 ACM.

关键词： network function virtualization

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Reinforcement Q-learning enabled energy-efficient service function chain provisioning in multi-domain networks

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PEER-TO-PEER networkING AND APPLICATIONS 2025年第1期18卷 26-26页

作者： Wang, Zhiying Huang, Guanhua Sun, Gang Yu, Hongfang Sun, Jian Univ Elect Sci & Technol China Key Lab Opt Fiber Sensing & Commun Minist Educ Chengdu 611731 Peoples R China

network function virtualization (NFV) technology is an efficient way to address the increasing difficulty of provisioning and managing network services. However, NFV-related service function chaining (SFC) deployment in multi-domain networks remains challenging, and there is still room for performance improvement. This paper investigates many heuristic algorithms in the same field and proposes a new method for dynamic SFC deployment in a multi-domain network. In our study, we combine a heuristic algorithm with reinforcement learning and divide the complex problem into several parts. This algorithm efficiently gives the SFC deployment scheme in the multi-domain network with subdomain privacy protection requirements and considers the energy savings of the multi-domain networks. Compared with the existing approach, the proposed algorithm has superiorities in terms of deployment success ratio, deployment profit, time efficiency, and energy consumption.

关键词： network function virtualization Service function chaining Energy-saving network service deployment Reinforcement Q-learning

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Neural Graphs: An Effective Solution for the Resource Allocation in NFV Sites interconnected by Elastic Optical networks 23

Neural Graphs: An Effective Solution for the Resource Alloca...

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23rd International Conference on Transparent Optical networks, ICTON 2023

作者： Eramo, V. Lavacca, F.G. Valente, F. Filippetti, V. Rosato, A. Verdone, A. Panella, M. Sapienza University of Rome DIET Via Eudossiana 18 Rome00184 Italy

ISBN: (纸本)9798350303032

The paper proposes and investigates neural graph-based solution for the prediction of the processing capacities needed by the Virtual network function Instances in a network function virtualization environment. The proposed solution is centralized and performed by the Orchestrator which: i) acquires the processing capacity values measured by the Virtual network function Manager;ii) builds neural graphs each one relative to a measure period and where each node of a graph represents a VNFI and it is labelled with the measured processing capacity of that VNFI;iii) evaluates the prediction of the processing capacities needed by each VNFI node by means of convolution operations that allow for a capture of spatial and temporal correlations of the processing capacities required by the VNFIs. Instead of applying regular convolutional and recurrent units, we formulate the problem on graphs and build the model with complete convolutional structures, which enable much faster training speed with fewer parameters. © 2023 IEEE.

关键词： network function virtualization

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Artificial Intelligence in virtualized networks: a journey

Artificial Intelligence in virtualized networks: a journey

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2023 Italia Intelligenza Artificiale - Thematic Workshops, Ital-IA 2023

作者： Fichera, Silvia Artale, Antonino Derstepanians, Arman Pannocchi, Luigi Cucinotta, Tommaso Vodafone Spa via Lorenteggio Milan20147 Italy Scuola Superiore Sant'Anna Piazza dei Martiri Pisa56100 Italy

This paper provides an overview of the research activities in the area of Artificial Intelligence applied to network function virtualization (NFV), carried out by Vodafone, jointly with Scuola Superiore Sant'Anna of Pisa. Artificial Intelligence techniques have been used on system-level data gathered from Virtual Machines (VMs) composing a multitude of Virtualized network functions (VNFs), to tackle a number of problems: from traffic forecasting for capacity planning and optimization, to the off-line analysis of the daily behavior of metrics to identify possible anomalous patterns, to a Near Real time (NRT) approach for metric prediction and anomaly detection, so to trigger prompt reaction of operators of the infrastructure and services. These problems become particularly challenging in the context of the Vodafone infrastructure, spanning across several data centers for NFV throughout a dozen European Countries. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： network function virtualization

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SDN and NFV-based multi-scenario electric 5G network slice management 5

SDN and NFV-based multi-scenario electric 5G network slice m...

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2023 5th International Conference on Information Science, Electrical, and Automation Engineering, ISEAE 2023

作者： Zeng, Shuyan Zhu, Sicheng Xiang, Xuchen Ma, Kaizhi Meng, Sachula China Electric Power Research Institute Co. Ltd. Beijing China

ISBN: (纸本)9781510667440

With the development of new electric system, the new multi-scenario electric services put forward more stringent and differentiated communication requirements. 5G communication with software-defined network (SDN) and network functions virtualization (NFV) technologies provides an efficient solution. In this paper, we firstly analyze the communication requirements of multi-scenario electric 5G services including control, acquisition and mobile application services. Then, we propose a SDN and NFV based slice management scheme of electric 5G communication network, which aims to minimize the total transmission delay by joint optimizing transmission power and network slice allocation under the delay and energy consumption constraints. Simulation results show the superior performance of the proposed scheme in convergence rate, total transmission delay, and differentiated communication demand guarantee for multi-scenario electric 5G services. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： network function virtualization

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Model Predictive Control for Automated network Assurance in Intent-Based networking enabled Service function Chains 36

Model Predictive Control for Automated Network Assurance in ...

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36th IEEE/IFIP network Operations and Management Symposium, NOMS 2023

作者： Avgeris, Marios Leivadeas, Aris Athanasopoulos, Nikolaos Lambadaris, Ioannis Falkner, Matthias Carleton University Department of Systems and Computer Engineering Ottawa Canada Ácole de Technologie Supérieure Department of Software and It Engineering Montreal Canada Queen's University School of Electronics Electrical Engineering and Computer Science Belfast United Kingdom Cisco Systems Ottawa Canada

ISBN: (纸本)9781665477161

Recent trends in network function virtualization (NFV) combined with Internet of Things (IoT) and 5G applications have reshaped the network service offering. In particular, Service function Chains (SFCs) can associate network functions with physical and virtual resources towards providing a complete network service. Concurrently, the management of a continuously expanding network and the fulfillment of the applications' requirements pave the way for autonomic network solutions. Intent Based networking (IBN) is a novel paradigm that aims to achieve the automatic orchestration of network services and the assurance of their performance. Accordingly, in this paper, we propose a novel automated network assurance model, based on Model Predictive Control, to guarantee the Quality of Service (QoS) and security requirements of multi-tenant and IBN-enabled SFCs. In this context, corrective decisions are proactively taken, in the form of incoming intent relocations among the SFCs. The results reveal that our model can assure with high probability the application requirements and minimize QoS violations. © 2023 IEEE.

关键词： network function virtualization

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network function Offloading on Programmable Switch with Sequential Pipelines 8

Network Function Offloading on Programmable Switch with Sequ...

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8th IEEE Information Technology and Mechatronics Engineering Conference, ITOEC 2025

作者： Chen, Yan Pang, Bo Gao, Deyun Yang, Dong Beijing Jiaotong University School of Electronic and Information Engineering Beijing China

ISBN: (纸本)9798331517915

network function virtualization (NFV) allows network functions (NFs) to be chained as a service function chain (SFC) and deployed on a number of servers through virtualization technology, enabling flexible processing of network functions. With the development of programmable switches in recent years, some switches, such as P4 switches, are also capable of processing NFs, which can effectively improve the throughput of the system and reduce the processing latency of SFCs. But current programmable switches can only allow packets to be processed in a fixed NF order. Such a feature creates new problems in situations where network SFC requests are in a dynamic randomized manner. Based on the above background, this paper proposes a policy algorithm for accelerating SFC processing based on P4 switches. Our scheme take into account the sequential requirements of SFCs and the sequential structure of the P4 switch pipeline, and uses multiple switches to jointly process SFCs, which is able to handle dynamically generated SFCs with superior performance. Compared with other algorithms, our algorithm is able to achieve lower latency. © 2025 IEEE.

关键词： High Performance network function virtualization P4 Service function Chain

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Throughput Optimization VNF Placement in Cloud Datacenter Considering Time-Varying Workload and Multi-Tenancy 29

Throughput Optimization VNF Placement in Cloud Datacenter Co...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Yue, Yi Sun, Shiding Zhang, Zhiyan Tang, Xiongyan Yang, Wencong Zhang, Xuebei China Unicom Research Institute Beijing China National Engineering Research Center of Next Generation Internet Broadband Service Application Beijing China Zhengzhou University School of Electrical Engineering Zhengzhou China

ISBN: (纸本)9798350330717

network service providers benefit greatly from network function virtualization (NFV), which allows them to outsource their network functions (NFs) to cloud data centers flexibly. This paper focuses on the Virtual network function (VNF) placement in cloud data centers while maximizing the network's accepted Service function Chain Requests (SFCRs). To optimize resource utilization, we consider two key factors that are often overlooked: time-varying workloads and VNF sharing based on multi-tenancy technology. We formulate the VNF placement problem as an Integer Linear Programming (ILP) model. To solve the ILP, we devise a Throughput Optimization Heuristic Solution (TOHS). Finally, we conduct a detailed numerical simulation and compare our results with contrasting schemes in the existing literature. Our evaluation shows that the performance of TOHS is near to results derived by ILP solver for small-scale problems. In addition, TOHS outperforms other solutions in various scenarios, resulting in higher network throughput and better utilization of network resources. © 2023 IEEE.

关键词： network function virtualization Resource allocation Service function Chain Throughput optimization Virtual network function

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Performance Impacts of Scaling Policies for virtual IP Multimedia Subsystem on the Cloud

Performance Impacts of Scaling Policies for virtual IP Multi...

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IEEE Conference on network function virtualization and Software Defined networks (IEEE NFV-SDN)

作者： Chung, Wu-Chun Liang, Han-Ting Wang, Yun-He Chung Yuan Christian Univ Dept Informat & Comp Engn Taoyuan 320 Taiwan

ISBN: (数字)9781665473347

ISBN: (纸本)9781665473347

In network function virtualization, mobile network functions are segregated from proprietary hardware to the commercial off-the-shelf computer on the cloud. This paradigm shift aims at reducing capital expenditures while improving the scalability of Virtual network functions (VNFs). Horizontal scaling and vertical scaling are two typical scaling policies. This paper investigates the performance impacts while adopting different types of scaling policies into a practical cloud system. A virtual IP Multimedia Subsystem (vIMS) is deployed on an OpenStack testbed for validating the VNF on-boarding. To evaluate the scaling performance of vIMS, the successful call rate is measured with a variety of resource capacities. Experimental results show that the performance of vertical scaling policy has a limitation when the instance size is getting larger. As an alternative, the horizontal scaling policy enhances the performance while increasing the number of instances. Based on the evaluations, a novel auto-scaling algorithm is further proposed to adapt the utilization of VNF instances. Results also verify the feasibility and effectiveness of the proposed algorithm with varied call rates.

关键词： Cloud Computing network function virtualization virtual IMS Scaling Policy

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