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13th International Conference on Experience of Designing and Application of CAD Systems in Microelectronics (CADSM)

作者： Skulysh, Mariia Klimovych, Oleg Natl Tech Univ Ukraine Kyiv Polytech Inst Inst Telecommun Syst Kiev Ukraine

ISBN: (纸本)9786176077169

In this paper the main aspects of usage network functions virtualization (NFV) in the domain of Evolved Packet Core (EPC) virtualization are given. Modern virtualization technologies in combination with existing tools for storage and computing, ensure virtualization and abstraction for the entire set of critical resources. The general aim of NFV is to deliver functions, networks and infrastructure as services rather than as features of vertically integrated systems. virtualization of EPC components using NFV approach can provide capacity support for mobile broadband services with high level of performance. For operators, the return on investment associated with migrating network services to the cloud comes in the form of a high degree of automation in network operation.

关键词： network functions virtualization Evolved Packet Core virtualization virtualized network functions

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Security-Aware Cost Optimized Dynamic Service Function Chain Scheduling

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JOURNAL OF network AND SYSTEMS MANAGEMENT 2025年第1期33卷 1-39页

作者： Dubba, Sudha Killi, Balaprakasa Rao Natl Inst Technol Dept Comp Sci & Engn Warangal 506003 Telangana India

The idea of network function virtualization has emerged recently as a means of accelerating the deployment of middleboxes and network operations while also lowering deployment costs. Service function chaining provides network connectivity and steers traffic between the deployed VNF instances to provide a network service. However, integrating NFV within SFC scheduling introduces complexities, particularly in efficiently allocating resources to VNFs amidst dynamic network traffic and service demands. Optimization of VNF placement and scheduling is essential to minimize execution costs while meeting stringent Service Level Agreements (SLAs) and ensuring quality-guaranteed services. Moreover, the convergence of NFV and SFC scheduling brings for security challenges, including unauthorized access, data interception, and service disruption. Balancing optimization objectives with stringent security requirements poses a non-trivial task, emphasizing the need for prioritizing security in resource allocation and scheduling decisions. Meeting SFC deadlines is challenging due to dynamic network conditions, service demands, and resource allocation complexity. Failure to meet deadlines can lead to service quality degradation, SLA violations, and financial penalties. To address these challenges, the security and cost-aware SFC scheduling problem is formulated as an optimization problem. Moreover, a three-level security model is designed for both the VNFs and the physical machines in the NFV-enabled networks. Since the problem is NP-hard, we propose two heuristics named Particle Swarm Optimization-Based SFC Scheduling approach and Group Learning Particle Swarm Optimization-Based SFC Scheduling model that focus on optimizing the execution cost of SFC while meeting security and deadline requirements. The proposed models are compared with the existing SFC scheduling models. The effectiveness of the proposed scheduling approaches is evaluated through extensive simulations and it is show

关键词： network functions virtualization Service function chain scheduling Virtual network function Dynamic scheduling Security Cost PSO service level agreement

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Priority-Aware Resource Allocation for VNF Deployment in Service Function Chains Based on Graph Reinforcement Learning

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Computers, Materials & Continua 2025年第5期83卷 1649-1665页

作者： Seyha Ros Seungwoo Kang Taikuong Iv Inseok Song Prohim Tam Seokhoon Kim Department of Software Convergence Soonchunhyang UniversityAsan31538Republic of Korea School of Digital Technologies American University of Phnom PenhPhnom Penh12106Cambodia Department of Computer Software Engineering Soonchunhyang UniversityAsan31538Republic of Korea

Recently,network functions virtualization(NFV)has become a critical resource for optimizing capability utilization in the 5G/B5G *** decomposes the network resource paradigm,demonstrating the efficient utilization of network functions(NFs)to enable configurable service priorities and resource *** Service Providers(TSPs)face challenges in network utilization,as the vast amounts of data generated by the Internet of Things(IoT)overwhelm existing *** applications,which generate massive volumes of diverse data and require real-time communication,contribute to bottlenecks and *** this context,Multiaccess Edge Computing(MEC)is employed to support resource and priority-aware IoT applications by implementing Virtual network Function(VNF)sequences within Service Function Chaining(SFC).This paper proposes the use of Deep Reinforcement Learning(DRL)combined with Graph Neural networks(GNN)to enhance network processing,performance,and resource pooling *** facilitates feature extraction through Message-Passing Neural network(MPNN)*** with DRL,Deep Q-networks(DQN)are utilized to dynamically allocate resources based on IoT network priorities and *** focus is on minimizing delay times for VNF instance execution,ensuring effective resource placement,and allocation in SFC deployments,offering flexibility to adapt to real-time changes in priority and *** results demonstrate that our proposed scheme outperforms reference models in terms of reward,delay,delivery,service drop ratios,and average completion ratios,proving its potential for IoT applications.

关键词： Deep reinforcement learning graph neural network multi-access edge computing network functions virtualization software-defined networking

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Design and Implementation of network virtualization Management System

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IEICE TRANSACTIONS ON COMMUNICATIONS 2014年第11期E97B卷 2286-2301页

作者： Katayama, Yohei Yamamoto, Takehito Tsukishima, Yukio Yamada, Kazuhisa Takahashi, Noriyuki Takahara, Atsushi Nakao, Akihiro NTT Corp NTT Network Innovat Labs Yokosuka Kanagawa 2390847 Japan Univ Tokyo Appl Comp Sci Interfaculty Initiat Informat Studies Grad Sch Interdisciplinary Informat Studies Tokyo 1130033 Japan Natl Inst Informat & Commun Technol NICT Koganei Tokyo 1848795 Japan

Due to the recent network service market trends, network infrastructure providers must make their network infrastructures tolerant of network service complexity and swift at providing new network services. To achieve this, we first make a design decision for the single domain network infrastructure in which we use network virtualization and separate the network service control and management from the network infrastructure and leave the resource connectivity control and management in the network infrastructure so that the infrastructure can maintain simplicity and the network service can become complex and be quickly provided. Along with the decision, we construct an architecture of the network infrastructure and a network management model. The management model defines a slice as being determined by abstracted resource requirements and restructures the roles and planes from the viewpoint of network infrastructure usability so that network service requesters can manage network resources freely and swiftly in an abstract manner within the authorities the network infrastructure operator provides. We give the details of our design and implementation for a network virtualization management system along with the model. We deployed and evaluated our designed and implemented management system on the Japan national R&E testbed (JGN-X) to confirm the feasibility of our management system design and discuss room for improvement in terms of response time and scalability towards practical use. We also investigated certain cases of sophisticated network functions to confirm that the infrastructure can accept these functions without having to be modified.

关键词： management system network virtualization future internet new generation network software designed network network functions virtualization

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Multi-Agent Deep Q-networks for Efficient Edge Federated Learning Communications in Software-Defined IoT

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Computers, Materials & Continua 2022年第5期71卷 3319-3335页

作者： Prohim Tam Sa Math Ahyoung Lee Seokhoon Kim Department of Software Convergence Soonchunhyang UniversityAsan31538Korea Department of Computer Science Kennesaw State UniversityMariettaGA 30060USA Department of Computer Software Engineering Soonchunhyang UniversityAsan31538Korea

Federated learning(FL)activates distributed on-device computation techniques to model a better algorithm performance with the interaction of local model updates and global model distributions in aggregation averaging ***,in large-scale heterogeneous Internet of Things(IoT)cellular networks,massive multi-dimensional model update iterations and resource-constrained computation are challenging aspects to be tackled *** paper introduces the system model of converging softwaredefined networking(SDN)and network functions virtualization(NFV)to enable device/resource abstractions and provide NFV-enabled edge FL(eFL)aggregation servers for advancing automation and ***-agent deep Q-networks(MADQNs)target to enforce a self-learning softwarization,optimize resource allocation policies,and advocate computation offloading *** gathered network conditions and resource states,the proposed agent aims to explore various actions for estimating expected longterm rewards in a particular state *** exploration phase,optimal actions for joint resource allocation and offloading decisions in different possible states are obtained by maximum Q-value ***-based virtual network functions(VNF)forwarding graph(VNFFG)is orchestrated to map VNFs towards eFL aggregation server with sufficient communication and computation resources in NFV infrastructure(NFVI).The proposed scheme indicates deficient allocation actions,modifies the VNF backup instances,and reallocates the virtual resource for exploitation *** neural network(DNN)is used as a value function approximator,and epsilongreedy algorithm balances exploration and *** scheme primarily considers the criticalities of FL model services and congestion states to optimize long-term *** results presented the outperformance of the proposed scheme over reference schemes in terms of Quality of Service(QoS)performance metrics,including packet

关键词： Deep Q-networks federated learning network functions virtualization quality of service software-defined networking

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Software-Defined Architectures and Technologies for Underwater Wireless Sensor networks: A Survey

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IEEE COMMUNICATIONS SURVEYS AND TUTORIALS 2018年第4期20卷 2855-2888页

作者： Luo, Hanjiang Wu, Kaishun Ruby, Rukhsana Liang, Yongquan Guo, Zhongwen Ni, Lionel M. Shandong Univ Sci & Technol Sch Comp Sci & Engn Qingdao 266510 Peoples R China Shenzhen Univ Dept Comp Sci & Engn Shenzhen 518060 Peoples R China Ocean Univ China Dept Comp Sci Qingdao 266100 Peoples R China Univ Macau Dept Comp & Informat Sci Macau Peoples R China

The ocean covers nearly two-thirds of the surface on the Earth, and there has been great interest in developing underwater wireless sensor networks (UWSNs) to help us explore the ocean realm. A great deal of efforts have been devoted to it, and significant progress has been made since the beginning of 2000s. However, most of the networks are isolatedly developed currently, inherently hardware-based and application-oriented with inflexible closed-form architectures, which are difficult to reconfigure, reprogram and evolve. They also lack the capability in sharing resources, and are far from service-oriented networks. These limitations impair their capacity for wide range of applications. To further propel the development of UWSNs, next-generation UWSNs have been proposed recently, which are robust, flexible, adaptive, programmable, support resource-sharing feature and are easy to manage and evolve. Moreover, a number of novel software-defined techniques and paradigms, such as software-defined radio, cognitive acoustic radio, network function virtualization, software-defined networking, Internet of Underwater Things, and sensor-cloud, have been emerging. These software-defined technologies have the capability of softwarizing network resources, and then redefining them to satisfy diverse application requirements, improve resource utilization efficiency and simplify network management. Consequently, these evolving technologies are envisioned as critical building blocks and major driving forces, which will transform conventional UWSNs toward software-based, programmable, user-customizable, and service-oriented next-generation UWSNs. In this paper, we provide a comprehensive review of existing works on implementing these techniques, and also present discussions for future research. We hope to inspire more active research on these areas and take a step further toward realizing next-generation UWSNs.

关键词： Underwater sensor networks software-defined networking software-defined radio software-defined acoustic modem software-defined cognitive network network functions virtualization

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FlexState: Flexible State Management of network functions

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IEEE ACCESS 2021年 9卷 46837-46850页

作者： Pozza, Matteo Rao, Ashwin Lugones, Diego F. Tarkoma, Sasu Univ Helsinki Dept Comp Sci Helsinki 00014 Finland Nokia Bell Labs Dublin D15 Y6NT 15 Ireland

network function (NF) developers have traditionally prioritized performance when creating new packet processing capabilities. This was usually driven by a market demand for highly available solutions with differentiating features running at line rate, even at the expense of flexibility and tightly-coupled monolithic designs. Today, however, the market advantage is achieved by providing more features in shorter development cycles and quickly deploying them in different operating environments. In fact, network operators are increasingly adopting continuous software delivery practices as well as new architectural styles (e.g., microservices) to decouple functionality and accelerate development. A key challenge in revisiting NF design is state management, which is usually highly optimized for a deployment by carefully selecting the underlying data store. Therefore, migrating to a data store that suits a different use case is time-consuming as it requires code refactoring and adaptation to new application programming interfaces, APIs. As a result, refactoring NF software for different environments can take up to months, reducing the pace at which new features and upgrades can be deployed in production networks. In this paper, we demonstrate experimentally that it is feasible to introduce an abstraction layer to decouple NF state management from the data store adopted while still approaching line-rate performance. We present FlexState, a state management system that exposes data store functionality as configuration options, which reduces code refactoring efforts. Experiments show that FlexState achieves significant flexibility in optimizing the state management, and accelerates deployment on new scenarios while preserving performance and scalability.

关键词： Noise measurement Scalability Production Reliability engineering Distributed databases Optimization Middleware Data storage systems middleboxes network functions network functions virtualization NFV parallel processing state management

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Managing a World of Things: A Report on APNOMS2017

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JOURNAL OF network AND SYSTEMS MANAGEMENT 2019年第2期27卷 541-549页

作者： Kim, Myung-Sup Oishi, Haruo Huang, Jiun-Long Ju, Hongtaek Yoshihara, Kiyohito Yi, Chih-Wei Choi, Taesang Korea Univ Sejong Ro 2511 Jochiwon 30019 Sejong South Korea Nippon Telegraph & Tel Corp 9-11 Midori Cho 3 Chome Musashino Tokyo 1808585 Japan NCTU 1001 Univ Rd Hsinchu Taiwan Keimyung Univ 1095 Dalgubeol Daero Daegu 42601 South Korea KDDI Res 2-1-15 Ohara Fujimino Saitama 3568502 Japan ETRI 218 Gajeong Ro Daejeon 34129 South Korea

This article presents a report on APNOMS2017, which was held on Sept. 27-29, 2017 in Seoul, Korea. The theme of APNOMS2017 was Managing a World of Things.

关键词： network operations and management Software defined network network functions virtualization World of things 5G management

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Online Stochastic Buy-Sell Mechanism for VNF Chains in the NFV Market

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2017年第2期35卷 392-406页

作者： Zhang, Xiaoxi Huang, Zhiyi Wu, Chuan Li, Zongpeng Lau, Francis C. M. Univ Hong Kong Dept Comp Sci Hong Kong Hong Kong Peoples R China Univ Calgary Dept Comp Sci Calgary AB T2N 1N4 Canada

With the recent advent of network functions virtualization (NFV), enterprises and businesses are looking into network service provisioning through the service chains of virtual network functions (VNFs), instead of relying on dedicated hardware middleboxes. Accompanying this trend, an NFV market is emerging, where NFV service providers create VNF instances, assemble VNF service chains, and sell them for the use of customers, using resources (computing, bandwidth) that they own or rent from other resource suppliers. Efficient service chain provisioning and pricing mechanisms are still missing, to charge assembled service chains according to demand and the supply of resources at any time. We propose an online stochastic auction mechanism for on-demand service chain provisioning and pricing at an NFV provider. Our auction takes in buy bids for service chains from multiple customers and sell bids from various resource suppliers to supplement the NFV provider's geo-distributed resource pool, with resource occupation/contribution durations. We extend online primal-dual optimization framework for handling both buyers and sellers, with a new competitive analysis. The online mechanism maximizes the expected social welfare of the NFV ecosystem (the NFV provider, customers and resource suppliers) with a good competitive ratio as compared with the expected offline optimal social welfare, while guaranteeing truthfulness in bidding, individual rationality for both buyers and sellers, and polynomial time for computation. We evaluate our mechanism through trace-driven simulation studies, and demonstrate a close-to-offline-optimal performance in expected social welfare under realistic settings.

关键词： Auction mechanism design online algorithms network functions virtualization

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Reliability-Aware Service Chaining In Carrier-Grade Softwarized networks

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2018年第3期36卷 558-573页

作者： Qu, Long Khabbaz, Maurice Assi, Chadi Ningbo Univ Dept Elect Engn & Comp Sci Ningbo 315211 Zhejiang Peoples R China Notre Dame Univ Louaizeh Dept Elect Comp & Communm Engn Zouk Mosbeh Lebanon Concordia Univ CIISE Dept Montreal PQ H3G 1M8 Canada

network Function virtualization (NFV) has revolutionized service provisioning in cloud datacenter networks. It enables the complete decoupling of network functions (NFs) from the physical hardware middle boxes that network operators deploy for implementing service-specific and strictly ordered NF chains. Precisely, NFV allows for dispatching NFs as instances of plain software called virtual network functions (VNFs) running on virtual machines hosted by one or more industry standard physical machines. Nevertheless, NF softwarization introduces processing vulnerability (e.g., failures caused by hardware or software, and so on). Since any failure of VNFs could break down an entire service chain, thus interrupting the service, the functionality of an NFV-enabled network will require a higher reliability compared with traditional networks. This paper encloses an in-depth investigation of a reliability-aware joint VNF chain placement and flow routing optimization. In order to guarantee the required reliability, an incremental approach is proposed to determine the number of required VNF backups. Through illustration, it is shown herein that the formulated single path routing model can be easily extended to support resource sharing between adjacent backup VNF instances. This paper advocates the absolute existence of a share-resource-based VNF assignment strategy that is capable of trading off all of the reliability, bandwidth, and computing resources consumption of a given service chain. A heuristic is proposed to work around the complexity of the presently formulated integer linear programming (ILP). Thorough numerical analysis and simulations are conducted in order to verify and assert the validity, correctness, and effectiveness of this proposed heuristic reflecting its ability to achieve very close results to those obtained through the resolution of the complex ILP within a negligible amount of time. Above and beyond, the proposed resource-sharing-based VNF placement sc

关键词： network functions virtualization reliability cloud datacenter optimization routing VNF NFV

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