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A low latency service function chain with SR-I/OV in software defined networks

WIRELESS networkS 2020年第6期26卷 4459-4475页

作者： Tseng, Huai-En Shen, Shan-Hsiang Natl Taiwan Univ Sci & Technol Taipei Taiwan

A network flow is required to be processed by multiple network functions such as PGW and SGW in mobile networks as a service function chain (SFC). Compared to hardware-based network functions, virtualized network functions are more flexible for deployment. Software defined network (SDN) provides a centralized network architecture to manage network resources and route the network flow among network functions in sequence and virtual machines are leveraged to deploy the network functions as network function virtualization (NFV). However, currently the performance of NFV suffers from I/O latency because packet processing causes lots of interrupts that decreases CPU utilization. To address the I/O latency issue, SR-I/OV network card is designed to replace OpenvSwitch in host machines to reduce the system interrupts. However, SR-I/OV is not compatible with existing SDN system, which is an important component in future 5G networks. Therefore, we propose an integrated architecture called the low latency service function chain from a wider perspective in system design to overcome main defects described above. We modify appropriate components in SR-I/OV driver and OpenvSwitch to dramatically reduce packet processing latency in SFC composed by several VNFs. Moreover, our design is compatible with SDN environment and benefited by central control.

关键词： SR-IOV Software-defined networking network function virtualization

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A Multi-Site NFV Testbed for Experimentation With SUAV-Based 5G Vertical Services

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IEEE ACCESS 2020年 8卷 111522-111535页

作者： Vidal, Ivan Nogales, Borja Valera, Francisco Gonzalez, Luis F. Sanchez-Aguero, Victor Jacob, Eduardo Cervello-Pastor, Cristina Univ Carlos III Madrid Dept Telemat Engn Madrid 28911 Spain IMDEA Networks Inst Madrid 28918 Spain Univ Basque Country Fac Engn Dept Commun Engn UPV EHU Bilbao 48013 Spain Univ Politecn Cataluna Dept Network Engn Barcelona 08860 Spain

With the advent of 5G technologies, vertical markets have been placed at the forefront, as fundamental drivers and adopters of technical developments and new business models. Small Unmanned Aerial Vehicles (SUAVs) are gaining traction in multiple vertical sectors, as key assets to generate, process, and distribute relevant information for the provision of value-added services. However, the enormous potential of SUAVs to support a flexible, rapid, and cost-effective deployment of vertical applications is still to be exploited. In this paper, we leverage our prior work on network functions virtualization (NFV) and SUAVs to design and build a multi-site experimentation testbed based on open-source technologies. The goal of this testbed is to explore synergies among NFV, SUAVs, and vertical services, following a practical approach primarily governed by experimentation. To verify our testbed design, we realized a reference use case where a number of SUAVs, cloud infrastructures, and communication protocols are used to provide a multi-site vertical service. Our experimentation results suggest the potential of NFV and SUAVs to flexibly support vertical services. The lessons learned have served to identify missing elements in our NFV platform, as well as challenging aspects for potential improvement. These include the development of specific mechanisms to limit processing load and delays of service deployment operations.

关键词： Cloud computing 5G mobile communication network function virtualization Hardware Software Servers virtualization network functions virtualization (NFV) open source MANO (OSM) small unmanned aerial vehicles (SUAV) test facilities vertical services

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Method of Routing functions virtualization in the Modern networks 8

Method of Routing Functions Virtualization in the Modern Net...

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8th International Scientific Conference "Information Technology and Implementation" Workshop, IT and I-WS 2021

作者： Nikolchev, Kyryl Ahafonov, Yurii Starkova, Olena Herasymenko, Kostiantyn Taras Shevchenko National University of Kyiv Volodymyrska St 60 Kyiv01601 Ukraine

The article discusses the existing routing methods, their advantages and disadvantages. It was discovered that to solve the routing methods disadvantages it is necessary to use the concept of network functions virtualization (ETSI ISG NFV). There were also showed the capabilities of future routing methods programming. © 2022 Copyright for this paper by its authors.

关键词： network function virtualization

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Techno-economic Assessment in Communications: Models for Access network Technologies

Techno-economic Assessment in Communications: Models for Acc...

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Future of Information and Communication Conference, FICC 2021

作者： Bendicho, Carlos Bilbao Spain

ISBN: (纸本)9783030730994

This article shows State of the Art of techno-economic modeling for access network technologies, presents the characteristics a universal techno-economic model should have, and shows a classification and analysis of techno-economic models in the literature based on such characteristics. In order to reduce the gap detected in the literature, the author created and developed a Universal Techno-Economic Model and the corresponding methodology for techno-economic assessment in multiple domains, currently available for industry stakeholders under specific licence of use. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： network function virtualization

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Neural network-Based Traffic Prediction Model with Adaptive Spatial-Temporal Analysis in NFV networks 21

Neural Network-Based Traffic Prediction Model with Adaptive ...

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21st IEEE International Conference on Communication Technology, ICCT 2021

作者： Yu, Fenglei Xu, Zhanqi Yang, Fan Du, Shuang School of Telecomm. Eng Xidian University Xi'an China

ISBN: (纸本)9781665432061

network function virtualization (NFV) aims at satisfying various performance requirements of network services and increasing the performance/cost ratio mostly by decoupling software and hardware. However, network operators in the NFV scenario are facing several challenges in allocating resources and reducing operating expenses due to traffic explosion, and traffic prediction is helpful for operators to tackle this issue. The available models only consider the spatial or temporal correlation among traffic flows, but fail to combine the two aspects. In this paper, a neural network-based model with adaptive spatial-temporal analysis is proposed to predict the future traffic in NFV networks. First, we use the Long Short-Term Memory (LSTM) model to predict the traffic matrixes by capturing the long-term dependency. Then, we put forward a new mechanism to consider the spatial-temporal correlation between the target flow and the other flows in each traffic matrix. Besides, we adaptively select the most relevant flows, which are used to modify the prediction result through the Back Propagation Neural network (BPNN). The experiments show that the proposed model can significantly improve the prediction accuracy compared to the available work. © 2021 IEEE.

关键词： network function virtualization

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Graph neural network-based virtual network function deployment optimization

Graph neural network-based virtual network function deployme...

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作者： Kim, Hee-Gon Park, Suhyun Lange, Stanislav Lee, Doyoung Heo, Dongnyeong Choi, Heeyoul Yoo, Jae-Hyoung Hong, James Won-Ki Department of Computer Science and Engineering POSTECH Pohang Korea Republic of Department of Information Security and Communication Technology NTNU Trondheim Norway Department of Information and Communication Engineering HGU P6aaohang Korea Republic of

Software-defined networking (SDN) and network function virtualization (NFV) help reduce the operating expenditure (OPEX) and capital expenditure (CAPEX) as well as increase the network flexibility and agility. However, since the network is more dynamic and heterogeneous than before, operators have problems to cope with the increased complexity of managing virtual networks and machines. This complexity is paired with strict time requirements for making management decisions;traditional mechanisms that rely on, for example, integer linear programming (ILP) models are no longer feasible. Machine learning has emerged as one of the possible solution to address network management problems to get near-optimal solutions in a short time. However, applying machine learning to network management is also not simple and has many challenges. Especially, understanding the network environment is an important problem for designing a machine learning model. In this paper, we proposed to use graph neural network (GNN) for virtual network function (VNF) management. The proposed model solves the complex VNF management problem in a short time and gets near-optimal solutions. We developed a model by taking into account various network environment conditions so that it can be applied in the actual network environment. Also, through in-depth experiments, we suggested the direction of the machine learning-based network management method. © 2021 John Wiley & Sons, Ltd.

关键词： network function virtualization

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An analysis on mission-driven networking technologies in data link 4

An analysis on mission-driven networking technologies in dat...

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4th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2021

作者： Yongqiong, Yuan Junfeng, Hu Liang, Zhang 20th Institute Xi’an China

ISBN: (纸本)9781665432030

At the end of the battlefield, the efficient networking among combat resources to ensure the real-time and reliable transmission of information is one of the keys to forming information superiority. network resources will become scarcer in contested environments. According to the mission characteristics and differentiated needs, making full use of the limited network resource to guarantee task is the focus of network attention. Therefore how to optimize the use of limited network resources based on the characteristics of tasks becomes a very important issue. According to the research results in tactical data link and civil mobile communication many researchers have contributed, we compare the representative mission-driven networking technologies and analyze their integral development. © 2021 IEEE

关键词： Analytical models network slicing Mobile communication Software Data models Real-time systems network function virtualization

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Edge-to-Cloud Collaborative for QoS Guarantee of Smart Cities

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IFAC-PapersOnLine 2022年第11期55卷 60-65页

作者： Jiaju Wang Wei Jian Baochuan Fu

With the rapid development of big data, cloud computing, mobile Internet and other new-generation information technologies, smart cities, carry more and more intelligent applications, and put forward higher requirements for data processing capacity and network service quality. The integration system of Edge-to-Cloud collaboration provides a feasible method to effectively improve network performance to adapt to the changing needs of users. However, the existing network management mechanism is difficult to adapt to the actual demand changes due to the characteristics of the edge-cloud fusion system, such as device diversity, location complexity and resource dynamics. This article to the idea of sliding mode control function of network virtualization technology and network, the study method and collaborative optimization theory as the foundation, of the application of static and dynamic models of the intelligence cities, fault prediction and fault tolerant management mechanism, task scheduling and resource allocation adaptive collaborative optimization mechanism, to ensure that the cities network real-time, reliability, and security, At the same time, combined with the smart campus platform of our school, the real-time performance and effectiveness of the network are tested and evaluated, providing a case demonstration for the intelligent application of smart cities. This project will further enrich and improve the theoretical system of end-to-end cloud collaborative optimization and provide new means and methods for intelligent cities network QoS(Quality of Service) guarantee.

关键词： Smart City Edge-to-Cloud Collaboration network function virtualization Task Scheduling Resource Allocation Task Offloading

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A review on Virtualized Infrastructure Managers with management and orchestration features in NFV architecture

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COMPUTER networkS 2022年 217卷

作者： Kaur, Karamjeet Mangat, Veenu Kumar, Krishan Panjab Univ Univ Inst Engn & Technol UIET Chandigarh India

Nowadays, network function virtualization (NFV) is a growing and powerful technology in the research community and IT world. Traditional computer networks consist of hardware appliances such as firewalls and load balancers, called middleboxes. The implementation of these hardware devices is a difficult task due to their proprietary nature. NFV proposes an alternative way to design and deploy network functions called Virtual network functions (VNFs) on top of the commercial hardware by leveraging virtualization technology. NFV offers many advantages such as flexibility, agility, reduced capital and operational expenditure over the traditional network architecture. With the emergence of VNF, NFV needs to add new features regarding life-cycle management and end-to-end orchestration of VNFs. To fulfill this demand, NFV introduced the NFV-MANO framework for the management and orchestration of VNFs and provide network services to users. The NFV-MANO consists of NFV Orchestrator (NFVO), VNF Manager (VNFM), and Virtualized Infrastructure Manager (VIM). This paper provides a comprehensive overview of Virtualized Infrastructure Managers with NFV orchestration and VNF Management for implementing Service function Chain (SFC) in NFV architecture. Further, this study critically analyzes relevant research articles and proposes a taxonomy to select an appropriate VIM based on Emulation, virtualization, Containerization, and Hybrid environment for reliable SFC provisioning. Finally, various use cases have been identified for selecting particular VIM according to the requirements of the application.

关键词： Virtualized Infrastructure Manager network function virtualization Service function Chain VNF manager Mininet OpenStack Kubernetes Virtual machine Container Docker Tacker Mini-NFV

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Optimized Sampling Strategies to Model the Performance of Virtualized network functions

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JOURNAL OF network AND SYSTEMS MANAGEMENT 2020年第4期28卷 1482-1521页

作者： Van Rossem, Steven Tavernier, Wouter Colle, Didier Pickavet, Mario Demeester, Piet Univ Ghent IDLab Dept Informat Technol Imec iGent TowerTechnol Pk Zwijnaarde 126 B-9052 Ghent Belgium

Modern network services make increasing use of virtualized compute and network resources. This is enabled by the growing availability of softwarized network functions, which take on major roles in the total traffic flow (such as caching, routing or as firewall). To ensure reliable operation of its services, the service provider needs a good understanding of the performance of the deployed softwarized network functions. Ideally, the service performance should be predictable, given a certain input workload and a set of allocated (virtualized) resources (such as vCPUs and bandwidth). This helps to estimate more accurately how much resources are needed to operate the service within its performance specifications. To predict its performance, the network function should be profiled in the whole range of possible input workloads and resource configurations. However, this input can span a large space of multiple parameters and many combinations to test, resulting in an expensive and overextended measurement period. To mitigate this, we present a profiling framework and a sampling heuristic to help select both workload and resource configurations to test. Additionally, we compare several machine-learning based methods for the best prediction accuracy, in combination with the sampling heuristic. As a result, we obtain a reduced dataset which can still model the performance of the network functions with adequate accuracy, while requiring less profiling time. Compared to uniform sampling, our tests show that the heuristic achieves the same modeling accuracy with up to five times less samples.

关键词： Sampling heuristic network function virtualization Performance profiling Machine learning Regression

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