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IEEE Global Communications Conference (GLOBECOM)

作者： Zheng, Shuya Ren, Zhiyuan Cheng, Wenchi Zhang, Hailin Xidian Univ State Key Lab Integrated Serv Networks Xian Peoples R China

ISBN: (纸本)9781728181042

Integrating network function virtualization (NFV) into Multi-Access Edge Computing (MEC) network has been proposed. In the NFV-enabled MEC network, Service function Chains (SFCs) are proposed to orchestrate Virtual network functions (VNFs) required by network Service Requests (NSRs) for adapting to the various NSRs. NSRs are initiated as a set of requests for VNFs, and those requests should be mapped onto specific VNF instances in the executing-order, which also means embedding dependence-aware SFCs into the physical network. It is extremely challenging to optimize the latency when embedding SFCs into the MEC network because the executing-order constraint of VNFs in SFCs causes trouble for measuring the latency of designed SFC embedding schemes. For these reasons, we investigate how to minimize the latency when embedding SFCs into the heterogeneous MEC network under the condition of considering the dependency and concurrency of VNFs. Above all, a resource management model based on graph theory, element graph, is proposed to express the dependency of various resources in the NFV-enabled MEC network, which overcomes the problems caused by heterogeneity. Furthermore, relying on graph theory, we propose a universal evaluating model that can flexibly measure the latency cost of any designed service chain. Depending on the element graph and evaluating model, the Genetic Algorithm (GA) is adopted to optimize the latency of embedding SFCs, which can adaptively orchestrate the optimal VNFs for any SFC to minimize the latency.

关键词： Multi-access edge computing network function virtualization virtual network function service function chain graph theory

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TeraFlow: Secured Autonomic Traffic Management for a Tera of SDN flows 30

TeraFlow: Secured Autonomic Traffic Management for a Tera of...

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Joint 30th European Conference on networks and Communications / 3rd 6G Summit (EuCNC/6G Summit)

作者： Vilalta, Ricard Munoz, Raul Casellas, Ramon Martinez, Ricardo Lopez, Victor de Dios, Oscar Gonzalez Pastor, Antonio Katsikas, Georgios P. Klaedtke, Felix Monti, Paolo Mozo, Alberto Zinner, Thomas Overby, Harald Gonzalez-Diaz, Sergio Lonsethagen, Hakon Pulido, Jose-Miguel King, Daniel Ctr Tecnol Telecomunicac Catalunya CTTC CERCA Castelldefels Spain Tel ID Madrid Spain UBITECH Athens Greece NEC Labs Europe Heidelberg Germany Chalmers Univ Technol Gothenburg Sweden Univ Politecn Madrid Madrid Spain Norwegian Univ Sci & Technol Trondheim Norway Atos Madrid Spain Telenor Fornebu Norway Volta Networks Barcelona Spain Old Dog Consulting Llangollen Wales

ISBN: (纸本)9781665415262

TeraFlow proposes a new type of secure, cloud-native Software Defined networking (SDN) controller that will radically advance the state-of-the-art in beyond 5G networks by introducing novel micro-services architecture, and provide revolutionary features for both flow management (service layer) and optical/microwave network equipment integration (infrastructure layer) by adapting new data models. TeraFlow will also incorporate security using Machine Learning (ML) and forensic evidence for multi-tenancy based on Distributed Ledgers. Finally, this new SDN controller shall be able to integrate with the current network function virtualization (NFV) and Multi-access Edge Computing (MEC) frameworks as well as to other networks. The target pool of TeraFlow stakeholders expands beyond the traditional telecom operators towards edge and hyperscale cloud providers.

关键词： Cloud computing Technological innovation Computer architecture Machine learning Optical fiber networks network function virtualization Telecommunications

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Towards 5G-ready Security Metrics

Towards 5G-ready Security Metrics

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IEEE International Conference on Communications (ICC)

作者： Zhao, Lianying Oshman, Muhammad Shafayat Zhang, Mengyuan Moghaddam, Fereydoun Farrahi Chander, Shubham Pourzandi, Makan Carleton Univ Ottawa ON Canada Ericsson Canada St Laurent PQ Canada

ISBN: (纸本)9781728171227

The fifth-generation (5G) mobile telecom network has been garnering interest in both academia and industry, with better flexibility and higher performance compared to previous generations. Along with functionality improvements, new attack vectors also made way. network operators and regulatory organizations wish to have a more precise idea about the security posture of 5G environments. Meanwhile, various security metrics for IT environments have been around and attracted the community's attention. However, 5G-specific factors are less taken into consideration. This paper considers such 5G-specific factors to identify potential gaps if existing security metrics are to be applied to the 5G environments. In light of the layered nature and multi-ownership, the paper proposes a new approach to the modular computation of security metrics based on cross-layer projection as a means of information sharing between layers. Finally, the proposed approach is evaluated through simulation.

关键词： Security Metrics network function virtualization 5G Attack Graph Cloud

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An MEC-based VNF Placement and Scheduling Scheme for AR Application Topology

An MEC-based VNF Placement and Scheduling Scheme for AR Appl...

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IEEE Wireless Communications and networking Conference (WCNC)

作者： Tseng, Hsueh-Wen Yang, Ting-Ting Hsu, Fang-Tzu Natl Chung Hsing Univ Comp Sci & Engn Taichung Taiwan Natl Def Univ Comp Sci & Engn Taoyuan Taiwan

ISBN: (纸本)9781728195056

Recently, application services have become more and more diversified as new technology advances. The applications of Augmented Reality (AR) have received great attention from academics and operators. However, the complex computing required for AR applications has caused service operators to face the problems of poor user experience due to insufficient computing resources. network function virtualization (NFV) enables operators to directly establish network functions on virtual machines and can flexibly adjust the number of each virtual network function (VNF) according to users' requirements. Thus, the system can reduce unnecessary waste of resources. In addition, we use multi-access edge computing (MEC) to provide computing resources. The edge server is close to users and reduces transmission cost of the system. This paper proposes an MEC-based VNF placement and scheduling scheme for AR applications. Considering the functional topology of AR applications, the compute-intensive application can provide good service quality for a large number of users within limited resources. The simulation shows that the proposed method can maintain good service quality as the number of user requests increases.

关键词： Augmented Reality network function virtualization Multi-access Edge Computing

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Flow Scheduling in a Heterogeneous NFV Environment using Reinforcement Learning 15

Flow Scheduling in a Heterogeneous NFV Environment using Rei...

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15th IEEE International Conference on networking, Architecture and Storage (NAS)

作者： Lin, Chun-Jen Luo, Yan Wang, Liang-min Chen, Li-De Univ Massachusetts Dept Elect & Comp Engn Lowell MA 01854 USA Intel Corp Santa Clara CA 95051 USA

ISBN: (纸本)9781728177441

network function virtualization (NFV) allows network functions executed on general-purpose servers or virtual machines (VMs) instead of proprietary hardware, greatly improving the flexibility and scalability of network services. Recent trends in using programmable accelerators to speed up NFV performance introduce challenges in flow scheduling in a dynamic NFV environment. Reinforcement learning (RL) trains machine learning models for decision making to maximize returns in uncertain environments such as NFV. In this paper, we study the allocation of heterogeneous processors (CPUs and FPGAs) to minimize the delays of flows in the system. We conduct extensive simulations to evaluate the performance of reinforcement learning based scheduling algorithms such as Advantage Actor Critic (A2C), Trust Region Policy Optimization (TRPO) and Proximal Policy Optimization (PPO), and compare with greedy policies. The results show that RL based schedulers can effectively learn from past experiences and converge to the optimal greedy policy. We also analyze in-depth how the policies lead to different processor utilization and flow processing time, and provide insights into these policies.

关键词： network function virtualization Virtual network function Scheduling Reinforcement Learning

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Edge intelligence for service function chain deployment in NFV-enabled networks

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COMPUTER networkS 2022年 219卷

作者： Khoshkholghi, Mohammad Ali Mahmoodi, Toktam Kings Coll London Ctr Telecommun Res London England

With evolution of network function virtualization (NFV), network services can be provided as service function chains (SCs), each consisting of multiple virtual network functions (VNFs). The deployment of SCs including placement of VNF instances and virtual links connecting these functions, onto the substrate physical network is a critical issue which significantly affects the performance of the offered network services. Due to the unpredictable traffic and network state variations, as well as diverse quality of service (QoS) requirements, an online SCs deployment approach is needed to cope with different service requests and real-time network traffics. In this paper, we employ edge intelligence using a distributed deep reinforcement learning approach to deploy SCs in order to jointly balance the load on the physical nodes and links in the edge environments. The evaluation results show that the proposed approach outperforms state-of-the-art algorithms in terms of minimizing the drop rate of the incoming service chain requests. In addition, the proposed approach is able to rapidly deploy service flows even in the large real-world network typologies.

关键词： Edge intelligence network function virtualization Service chain deployment Markov decision process Distributed deep reinforcement learning

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A MEC architecture for a better quality of service in an Autonomous Vehicular network

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COMPUTER networkS 2022年 219卷

作者： Sindjoung, Miguel Landry Foko Velempini, Mthulisi Bomgni, Alain Bertrand Univ Limpopo Dept Comp Sci Mankweng South Africa Univ Dschang Fac Sci Dschang Cameroon Univ South Dakota Dept Biomed Engn Vermillion SD USA

Designing 5G networks and related applications such as the Internet of Things (IoT), Cellular and autonomous vehicular networks (AVNET) is a challenge. Indeed, these networks are subjected to a number of constraints that play a crucial role in the network's quality of service (QoS). Among these constraints, we have the management of computing, storage, bandwidth resources and low latency requirements. If in the past cloud computing has been used to avoid networks being affected by some of the previous constraints, that technology negatively affects the low latency requirements required by AVNETs for example. Multi-access Edge Computing (MEC) has recently emerged as a palliative solution to cloud computing. MEC aims to bring computing and storage resources from Cloud Data Center to Edge Data Center nearer to the User Equipment (UEs) in order to reduce the UEs' requests latency for an improvement of the network's QoS. Many MEC architectures have been proposed for AVNET. These solutions make use of Software Defined networking (SDN), network function virtualization (NFV), Service function Chaining (SFC) or network Slicing (NS) technologies. Some of these techniques combine partially these technologies while others do not. But to the best of our knowledge, none of them combines all these technologies to obtain a better QoS. In this paper, we combine the SDN, NFV, SFC and NS technologies to efficiently manage the MEC server resources for guaranteeing the QoS requirements in AVNETs. The QoS parameters we consider are latency, computing, storage and bandwidth resources. In that way, we first present a MEC server mathematical resource management model, then, we propose a new MEC architecture adapted to AVNETs that uses the aforementioned technologies also as the mathematical model we first present to manage the bandwidth, computing, and storage resources. The simulation results show that these resources are well managed, resulting to a low end to end latency for autonomous v

关键词： Autonomous vehicular network Cloud computing Multi-access Edge Computing network function virtualization network Slicing Quality of service Service function Chaining Software Defined networking

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FPGA-accelerated SmartNIC for supporting 5G virtualized Radio Access network

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COMPUTER networkS 2022年 210卷 1页

作者： Borromeo, Justine Cris Kondepu, Koteswararao Andriolli, Nicola Valcarenghi, Luca Scuola Super Sant Anna Via Moruzzi 1 I-56124 Pisa Italy Indian Inst Technol Dharwad Dharwad Karnataka India Natl Res Council Italy CNR IEIIT via Caruso 16 I-56122 Pisa Italy

Disaggregated, virtualized, and open next-generation eNodeB (gNB) could bring several benefits to the Next Generation Radio Access network (NG-RAN) by enabling more market competition and customer choice, lower equipment costs, and improved network performance. This can be achieved through gNB-central unit (CU) control plane (CP), gNB-CU-user plane (UP) and gNB-distributed unit (DU) separation, CU and DU function virtualization, and zero touch RAN management and control. However, to achieve the performance required by specific foreseen 5G usage scenarios (e.g., Ultra Reliable Low Latency Communications - URLLC), offloading selected disaggregated gNB functions into an accelerated hardware becomes a *** this aim, this study proposes the implementation of 5G DU Low-PHY layer functions into an FPGAbased SmartNIC exploiting the Open Computing Language (OpenCL) framework to facilitate the integration of accelerated 5G functions within the mobile protocol stack. The proposed implementation is compared against (i) a CPU-based OpenAirInterface implementation, and (ii) a GPU-based implementation of IFFT exploiting clfft and cufft libraries. Experimental results show that the different optimization techniques implemented in the proposed solution reduce the Low-PHY processing time and the use of FPGA resources. Moreover, the GPU-based implementation of the cufft and the proposed FPGA-based implementation have a lower processing time and power consumption compared to a CPU-based implementation for up to two cores. Finally, the implementation in a SmartNIC reduces the delay added by the host-to-device communication through the Peripheral Component Interconnect Express (PCIe) interface, considering both functional split options 2 and 7-1.

关键词： Hardware Acceleration network function virtualization OpenCL

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An SDN/NFV based Intelligent Fog Architecture for DDoS Defense in Cyber Physical Systems 10

An SDN/NFV based Intelligent Fog Architecture for DDoS Defen...

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10th International Conference on System Modeling and Advancement in Research Trends, SMART 2021

作者： Snehi, Manish Bhandari, Abhinav Computer Science and Engineering Punjabi University Punjab Patiala India

ISBN: (纸本)9781665439701

The Internet of Things (IoT) has garnered considerable interest in recent years as its technical capabilities have facilitated the creation of a diverse variety of commercial revenue models and services (e.g., medical cyber-physical systems, smart agriculture, Industry 4.0, smart cities, etc.). However, the security gaps in intelligent systems continue to be a significant source of concern. Malevolent attackers employ attacks like distributed denial of service (DDoS) to weaken system availability. To mitigate attack traffic, adopting a modern Software-defined networked backbone and network function virtualization (NFV) paradigm has proven to be a potential approach. This paper offers a comprehensive examination of the cutting-edge defense solutions driven by contemporary SDN/NFV technologies, highlighting the key limitations and future scope. The paper also presents the multi-dimensional view of the defense architecture by examining the Internet of Things (IoT) scenarios, defense strategies, the role of Fog to overcome research gaps, and leveraging SDN/NFV architecture for an intelligent defense solution. Furthermore, the paper examines the profound network backbone and offers the intelligent Machine and Deep learning-based distributed DDoS defense solution deployed in the Fog layer. The article concludes with an evaluation of open issues and research prospects for vulnerability apprehension in Smart systems. Keywords - SDN, Software Defined network, NFV, network functions virtualization, Cloud, IoT, Fog Computing, Distributed Denial of Service, DDoS © 2021 IEEE.

关键词： network function virtualization

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Security Service function Chain Deployment Using a Viterbi-Based Algorithm 13

Security Service Function Chain Deployment Using a Viterbi-B...

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13th IEEE International Conference on Communication Software and networks (ICCSN)

作者： Zhai, Dong Meng, Xiangru Kang, Qiaoyan Hu, Hang Meng, Qingwei Liang, Yuan Air Force Engn Univ Informat & Nav Coll Xian 710077 Shaanxi Peoples R China Air Force Engn Univ Aeronaut Engn Coll Xian 710038 Shaanxi Peoples R China

ISBN: (纸本)9781665431828

network function virtualization (NFV) decouples network functions from hardware, improves the flexibility of resource allocation, and enhances network scalability. However, NFV also introduces several security threats since it relies on software, which makes attacking it or manipulating its services easier than having the network functions provided by hardware only. So security problem is a major concern for network operators and NFV users. This paper proposes a security and delay optimization service function chain (SFC) deployment method based on Viterbi algorithm. The proposed method considers the security demand level and transmission delay. Experiment results show that the proposed method not only has the best acceptance ratio, but also improves the virtual network function security level match degree and reduces the average transmission delay.

关键词： network function virtualization service function chain security Viterbi algorithm

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