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Optimizing differentiated SFCs of slicing using virtual/physical network resources for SDN-based flowing and steering in B5G/5G networking

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COMPUTER networkS 2025年 259卷

作者： Chang, Ben-Jye Lin, Yu-Ting Natl Yunlin Univ Sci & Technol Dept Comp Sci & Informat Engn Touliu Taiwan

For differentiating and customizing different types of flows and virtualizing physical resources of networks and machines, B5G/5G specifies several novel mechanisms, including VNF, SDN, Service function Chaining, network Slicing, MEC, etc. In B5G/5G, the out-of-band contention based random access using PHY subframe preambles is specified before data transmissions. However, B5G/5G requires dynamically efficient approaches for realizing real 5G, including randomly contending limited sharing channel preambles, dynamically determining flow slicing of SFC, dynamically determining PM/VNFi/VNFc resources, while minimizing carrying cost and energy consumption via multi-link/multi-path B5G network. Thus, this paper proposes the Optimizing Differentiated SFCs of Slicing Using Virtual/Physical network Resources for SDN-based Flowing and Steering in UL Random Access in B5G/5G (namely ODS). ODS consists of two phases: 1) Adaptive determining Service function Chaining (SFC) of Predictive Flowing according to diverse types of SDN-based Slicing (sPFS) and 2) B5G Cooperating SDN/ NFV-based Dynamic Flow Steering (cDFS). Numerical results indicating ODS outperforms the compared works in several performance metrics, including average access delay, E2E delay, the carrying cost, net-profit, loss probability, throughput, energy consumption cost and hit rate of flow steering. Consequently, several contributions have been achieved. First, B5G/5G adaptive segment routing with SDN is realized for multi-link, multi- path configurations in customized B5G networks. Second, a cost-reward-function mechanism is proposed as the optimal algorithm for handling diverse additive and non-additive QoS requirements. Third, the optimal service function chain (SFC) for PM/VNFi/VNFc is adaptively determined, minimizing cost and maximizing net profit for network slicing. Finally, the system dynamically determines the optimal computing tier and steers data flow efficiently.

关键词： B5G/5G network network function virtualization network slicing Software-defined networking Traffic steering Segment routing

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Contributions to the virtualization of the BNG

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IEEE ACCESS 2025年 13卷 18713-18733页

作者： Proenca, Jorge Figueiredo, Ricardo Pereira, Vasco Cruz, Tiago Simoes, Paulo Univ Coimbra Ctr Informat & Syst Univ Coimbra CISUC Dept Engn Informat DEI P-3030290 Coimbra Portugal

The Border network Gateway (BNG) assumes a pivotal role within the telecommunications network operator domain, particularly in broadband access services, by establishing and managing subscribers' connections. It serves as a crucial component, being responsible for various essential services that allow subscribers' connections and help optimizing infrastructure resources, including enforcing QoS policies and implementing Access Control Lists to safeguard against unauthorized access. Similarly to other elements within the operators' infrastructure, the BNG has faced escalating challenges due to the surge in bandwidth demand, rapid subscriber growth, and the introduction of novel services with unique requirements. As a single point of failure for subscriber-operator access, it becomes crucial to enhance management flexibility, simplify the device, and improve overall resilience. Consequently, there has been a growing interest among operators in virtualizing the BNG, following a trajectory which is similar to the virtualization of other telecommunications networks devices, such as the residential gateway. This paper examines the case for virtualizing the BNG, starting with an analysis of the underlying motivations driving this virtualization effort. Next, it provides an overview of the State-of-Art, highlighting the current proposals and advances related with the Virtual Border network Gateway (vBNG) concept. Furthermore, it proposes a reference vBNG architecture, also exploring the seamless integration with a virtual Customers' Premise Equipment infrastructure. Finally, a practical Proof-of-Concept is presented and used to assess the feasibility of the vBNG concept.

关键词： Logic gates Protocols Hardware Software Resilience Computer architecture Complexity theory Quality of service Central office Broadband communication Border network gateway virtualization broadband networks network function virtualization software defined networks telecommunications network operator

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Provably Efficient Service function Chain Embedding and Protection in Edge networks

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IEEE TRANSACTIONS ON networkING 2025年第1期33卷 178-193页

作者： Zheng, Danyang Cao, Xiaojun Southwest Jiaotong Univ Sch Comp & Artificial Intelligence Chengdu 611756 Sichuan Peoples R China Georgia State Univ Dept Comp Sci Atlanta GA 30302 USA

Internet-connected devices generate service function chain (SFC) requests for reliability-sensitive applications such as smart factories and intelligent healthcare. To facilitate reliable SFC provisioning, one can employ dedicated SFC protection approaches to protect the primary service function path (SFP) by constructing a fault-disjointed backup SFP. Notably, the construction processes of the fault-disjointed primary and backup SFPs are interdependent, and the direct application of existing SFC embedding approaches to construct these SFPs by separate processes may not effectively optimize overall resource consumption. In this work, for the first time, we comprehensively study how to embed and protect an SFC through collaborative processes that have provable bounds. We formally define the problem of SFC embedding and protection (SFCEP), for which we develop the novel techniques of a backup SFP identifier (BSI) and resource-aware Bellman-Ford loop (RBL) to address the challenges posed by collaborative embedding and protection. On the basis of these techniques, we propose an efficient algorithm called optimal SFC embedding and protection (Opt-SEP). When the network resources are sufficient to accommodate an incoming SFC request, we prove that Opt-SEP can minimize the overall resource cost of creating a pair of fault-disjointed primary and backup SFPs. Moreover, for cases in which the network resources are limited, our extensive simulation results show that Opt-SEP significantly outperforms the benchmarks.

关键词： Reliability Protection Heuristic algorithms Object recognition Service function chaining Reliability theory Firewalls (computing) Bandwidth Smart manufacturing Monitoring network function virtualization reliable service function chain dedicated protection exact algorithm

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Joint optimization of UPF placement and traffic routing for 5G core network user plane

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COMPUTER COMMUNICATIONS 2024年 216卷 86-94页

作者： Chen, Songyan Chen, Junjie Li, Hongjun Nanjing Univ Informat Sci & Technol Sch Comp Sci Nanjing Peoples R China Nantong Univ Sch Informat Sci & Technol Nantong Peoples R China Nantong Res Inst Adv Commun Technol Nantong Peoples R China

This paper investigates the dynamic deployment of the 5G core network user plane functions (UPFs) in the edge network under time-varying traffic conditions. The objective is to minimize the total cost, including energy consumption, user plane latency, and UPF deployment costs by jointly optimizing UPF placement and traffic routing over the entire planning horizon. We formulate the optimization problem as a mixed-integer linear programming (MILP) problem, which is proven to be NP-hard. To obtain the optimal solution for the problem, we propose a Benders decomposition-based algorithm. However, the high computational complexity of this algorithm limits its practical applicability for large-scale networks. Therefore, we propose a low-complexity algorithm based on nested Benders decomposition that can solve the problem suboptimally. The simulation results demonstrate the convergence and computational efficiency of the proposed algorithm and show that it outperforms two existing algorithms. Moreover, we demonstrate that cost-saving can be achieved by using more power-efficient servers or deploying more servers. Additionally, we show that adjusting the cost parameters can achieve a good tradeoff between energy consumption and user plane latency.

关键词： 5G core network network function virtualization UPF placement and traffic routing Nested benders decomposition

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Cost and Latency Customized SFC Deployment in Hybrid VNF and PNF Environment

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IEEE TRANSACTIONS ON network AND SERVICE MANAGEMENT 2024年第4期21卷 4312-4331页

作者： Li, Xin Zhou, Hui Ma, Lirong Xin, Jingjie Huang, Shanguo Beijing Univ Posts & Telecommun Sch Elect Engn Beijing 100088 Peoples R China

The SFC deployment problem has proved to be NP-hard and has attracted great research interests. At present, most existing studies focus on deploying SFC through virtual network functions (VNFs) and few studies involve hybrid VNF and physical network function (PNF) environment. However, in the transition to a comprehensive network function virtualization (NFV) network, hybrid VNF and PNF environment is possible and important. Currently, VNF and PNF both play an important role in today's cloud networks. PNF is far superior in processing speed, but VNF has advantages in flexibility and cost. Using VNF or PNF alone may not meet user needs, affecting user experience and system performance. Hence, this paper studies the SFC deployment problem in hybrid VNF and PNF environment. A cost and latency customized dynamic SFC deployment (CL-SFCD) scheme is proposed. Instead of giving priority to the PNF or the VNF roughly, the CL-SFCD scheme maps network functions to VNFs or PNFs according to the SFC requester's personalized demands to satisfy the demands of different users. It aims to minimize the weighted value of total cost and latency. The CL-SFCD scheme is formulated as a mixed integer linear programming (MILP) model for exact results. Heuristic algorithms are developed to provide an approximate optimal solution in large-scale cloud networks. Numerical results show that the CL-SFCD scheme achieves performance that balances cost and latency based on user requirements than the VNF-only,VNF-GA, and PNF-only deployment schemes.

关键词： Costs Hardware Cloud computing network function virtualization virtualization Symbols Scalability Mixed integer linear programming (MILP) network function virtualization (NFV) physical network function (PNF) service function chain (SFC) virtual network functions (VNF)

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Revealing the Impact of Dynamic Traffic on NFV networks Planned Under Static Assumptions

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IEEE ACCESS 2024年 12卷 104490-104502页

作者： Ruiz, Lidia de Miguel, Ignacio Duran Barroso, Ramon J. Carlos Aguado, Juan Merayo, Noemi Hortelano, Diego Fernandez, Patricia Univ Valladolid Dept Signal Theory Commun & Telemat Engn Valladolid 47002 Spain Univ Rey Juan Carlos Dept Comp Sci & Stat Mostoles 28933 Spain

5G/6G networks offer high-capacity, low-latency and high-speed communications to new services associated with vertical industries like smart cities, automotive and energy sectors. To achieve this objective, new networking and computing paradigms such as network function virtualization (NFV), Multi-access Edge Computing (MEC) and Software Defined networking (SDN) are required to bring flexibility and adaptability to networks, while optical networks are envisioned to build the backhaul of 5G/6G networks thanks to their high capacity. Current studies on NFV-5G network planning with MEC resources follow either the online trend or the offline trend. In the online trend, resource allocation to service connection requests is determined upon request arrival based on the available resources. Conversely, in the offline trend, network planning is conducted assuming that the expected traffic (or the full set of service requests) is known in advance. However, to the best of our knowledge, previous works have not assessed the performance of these static offline network plannings when operating under dynamic traffic. In this paper, we evaluate the performance of a previously proposed static planning algorithm for NFV-5G networks under dynamic traffic conditions and analyze the impact of dynamic traffic on the request blocking ratio. Moreover, we also examine the performance of the static planning for each individual service type in a dynamic network scenario with three different available services. The simulation results show that overdimensioning is necessary when planning NFV-5G networks statically, and that the overdimensioning should consider different criteria based on the network expected performance objectives.

关键词： Costs Planning Optical fiber networks Heuristic algorithms Routing Vehicle dynamics Resource management 5G mobile communication 6G mobile communication Telecommunication traffic network function virtualization Smart cities Software defined networking NFV MEC SDN WDM static planning dynamic traffic

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Cost-Efficient Cluster Migration of VNFs for Service function Chain Embedding

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IEEE TRANSACTIONS ON network AND SERVICE MANAGEMENT 2024年第1期21卷 979-993页

作者： Afrasiabi, Seyedeh Negar Ebrahimzadeh, Amin Promwongsa, Nattakorn Mouradian, Carla Li, Wubin Recse, Akos Szabo, Robert Glitho, Roch H. Concordia Univ Concordia Inst Informat Syst Engn Montreal PQ H3G 1M8 Canada Ericsson Res Montreal PQ H4S 0B6 Canada Eotvos Lorand Univ Fac Informat H-2314 Budapest Hungary Ericsson Res H-1117 Budapest Hungary Univ Western Cape Comp Sci Programme ZA-7535 Cape Town South Africa

network function virtualization (NFV) is a network architecture that separates network functions from dedicated hardware, implementing them as software modules known as Virtual network functions (VNFs), which are executed in virtual machines or containers. NFV increases the deployment flexibility and agility within operator networks and reduces the operating and capital expenditures significantly. In NFV, migration of VNFs can significantly reduce the embedding cost. However, stringent latency requirements between VNFs can make them tightly coupled, thus hindering each VNF from being migrated individually, and resulting in poor performance. One of the main challenges in an NFV environment is therefore to migrate a cluster of VNFs to minimize the embedding cost. In this paper, we aim to solve the problem of cluster VNF migration by considering the given inter-VNF latency requirements. We formulate the VNF migration problem as an Integer Linear Programming (ILP) and present two scalable and efficient algorithms for migrating a cluster of VNFs. Through extensive experiments, we show that our proposed algorithms are highly effective. They reduce the total embedding cost by 14% compared to the existing heuristics, while being much more scalable in terms of execution time compared to the brute-force approach.

关键词： virtualization network function virtualization VNF migration service function chain embedding virtual network function

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Priority-Aware Deployment of Autoscaling Service function Chains Based on Deep Reinforcement Learning

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IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND networkING 2024年第3期10卷 1050-1062页

作者： Yu, Xue Wang, Ran Hao, Jie Wu, Qiang Yi, Changyan Wang, Ping Niyato, Dusit Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol Nanjing 211106 Peoples R China Nanjing Univ Aeronaut & Astronaut Collaborat Innovat Ctr Novel Software Technol & In Nanjing 211106 Peoples R China York Univ Lassonde Sch Engn Dept Elect Engn & Comp Sci Toronto ON M3J1P3 Canada Nanyang Technol Univ Sch Comp Sci & Engn Singapore Singapore

Communication networks are being restructured by means of network function virtualization (NFV) and service-based architecture (SBA) to embrace greater flexibility, agility, programmability and efficiency. The deployment of service function chains (SFCs) to flexibly offer diverse network services is considered essential in NFV-based networks. Beyond the fifth-generation (5G) and sixth-generation (6G) eras, SFC deployment should be capable of satisfying various quality of service (QoS) requirements, coping with dynamic network states and traffic, handling urgent business in a timely manner, and avoiding resource congestion, all of which present significant scheduling challenges. In this paper, we propose a priority-aware deployment framework for autoscaling and multi-objective SFCs, which mainly includes 2 parts. First, to guarantee the diverse QoS requirements (e.g., latency and request acceptance rate) of various network services, a multi-objective SFC deployment scheme is established to optimize the service latency, deployment cost and service acceptance rate. Second, a deep reinforcement learning (DRL) algorithm, named the autoscaling and priority-aware SFC deployment algorithm (APSD), is further designed to solve the multi-objective optimization problem, which is NP hard. In APSD, we first prioritize requests with varying real-time characteristics to ensure that urgent services can be processed in a timely manner;based on the resiliency characteristics of virtual network functions (VNFs), we propose a hybrid scaling strategy to scale VNFs both horizontally and vertically to respond to changes in service requests and workload. We report comprehensive experiments carried out to assess the effectiveness of the proposed SFC deployment framework and demonstrate its advantages over its counterparts. Thus, we show that APSD is time efficient in solving the multi-objective optimization problem and that the obtained strategy always consumes the least resources (e.g., cen

关键词： Heuristic algorithms Real-time systems Quality of service Costs Resource management Adaptation models Scalability network function virtualization deep reinforcement learning service function chain priority-aware autoscaling

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Energy-Aware Positioning Service Provisioning for Cloud-Edge-Vehicle Collaborative network Based on DRL and Service function Chain

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2024年第4期23卷 3424-3435页

作者： Zhang, Peiying Zhang, Yi Kumar, Neeraj Guizani, Mohsen Barnawi, Ahmed Zhang, Wei China Univ Petr East China Qingdao Inst Software Coll Comp Sci & Technol Qingdao 266580 Shandong Peoples R China Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Shaanxi Peoples R China Thapar Inst Engn & Technol Dept Comp Sci & Engn Patiala 147004 Punjab India Univ Petr & Energy Studies Sch Comp Sci Dehra Dun 248007 Uttarakhand India Lebanese Amer Univ Dept Elect & Comp Engn Beirut 11022801 Lebanon Graphic Era Univ Dept Comp Sci & Engn Dehra Dun 248002 Uttarakhand India King Abdulaziz Univ Fac Comp & IT Jeddah 21577 Saudi Arabia Chandigarh Univ Dept Comp Engn Chandigarh 442606 India Mohamed Bin Zayed Univ Artificial Intelligence MBZ Machine Learning Dept Abu Dhabi 999041 U Arab Emirates King Abdulaziz Univ Fac Comp & Informat Technol Jeddah 21589 Saudi Arabia Qilu Univ Technol Shandong Acad Sci Shandong Comp Sci Ctr Natl Supercomp Ctr JinanComp Sci Ctr Jinan 250013 Shandong Peoples R China

In the collaborative intelligent transportation system, providing precise positioning services is costly. Reducing resource consumption and improving revenue are crucial to the development of positioning services. Therefore, a practical algorithm that combines cloud and edge network environments is necessary to improve the positioning services. Integrating network function virtualization and edge computing can provide users with more flexible and efficient services. Based on the above issues, we use the service function chain (SFC) to improve the positioning services provided in cloud-edge-vehicle collaborative networks (CEVCN). We propose a deep reinforcement learning-assisted SFC embedding algorithm and improve its performance through training. We construct a five-layer policy network to sense the environment of CEVCN and derive the optimal node selection strategy. Finally, we use the breadth-first search algorithm to solve the embedding scheme for virtual links. The simulation results show that our proposed algorithm has excellent performance. The long-term average revenue is improved by 21%, the long-term average revenue-cost ratio is improved by 13%, and the embedding rate is improved by 8%.

关键词： Cloud-Edge-Vehicle collaborative network deep reinforcement learning network function virtualization positioning service service function chain

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Service Deployment for Parallelized function Chains Considering Traffic-Dependent Delay

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IEEE TRANSACTIONS ON network AND SERVICE MANAGEMENT 2024年第2期21卷 2266-2286页

作者： Zhang, Chenlu Sato, Takehiro Oki, Eiji Kyoto Univ Grad Sch Informat Kyoto 6068501 Japan

In network function virtualization, virtual network functions (VNFs) are usually chained in specific orders to generate service function chains (SFCs). Recently, SFC parallelism has been presented to enable VNFs to run in parallel to reduce the end-to-end service delay. Existing works handle the issue of unbalanced parallel branches by assuming predefined linear delay models, which have limitations in efficient resource allocation and deployment cost savings. This paper proposes a deployment model for parallelized SFC that handles the imbalance issue with considering that the delay of each VNF depends on both arriving traffic and allocated computing resources, to improve the flexibility of computing resource allocation. We consider a non-linear relationship between delay, allocated computing resources, and arriving traffic. We apply VNF sharing to improve the efficiency of resource allocation. We formulate the proposed model as a mixed integer second-order cone programming problem (MISOCP) to minimize the total deployment cost, with satisfying the end-to-end delay requirement. We also introduce a heuristic algorithm to solve the original problem, because the MISOCP approach is intractable to handle larger-size problems in practical time. Numerical results show that the proposed model achieves lower deployment cost than the baseline models.

关键词： network function virtualization service deployment SFC parallelism VNF sharing queueing systems

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