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network function placement in Virtualized Radio Access network with Reinforcement Learning Based on Graph Neural network

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ELECTRONICS 2025年第8期14卷 1686-1686页

作者： Yi, Mengting Lin, Mugang Chen, Wenhui Hengyang Normal Univ Coll Comp Sci & Technol Hengyang 421008 Peoples R China Hengyang Normal Univ Hunan Engn Res Ctr Cyberspace Secur Technol & Appl Hengyang 421002 Peoples R China Hunan Prov Key Lab Intelligent Informat Proc & App Hengyang 421008 Peoples R China

In 5G and beyond 5G networks, function placement is a crucial strategy for enhancing the flexibility and efficiency of the Radio Access network (RAN). However, demonstrating optimal function splitting and placement to meet diverse user demands remains a significant challenge. The function placement problem is known to be NP-hard, and previous studies have attempted to address it using Deep Reinforcement Learning (DRL) approaches. Nevertheless, many existing methods fail to capture the network state in RANs with specific topologies, leading to suboptimal decision-making and resource allocation. In this paper, we propose a method referred to as GDRL, which is a deep reinforcement learning approach that utilizes graph neural networks to address the functional placement problem. To ensure policy stability, we design a policy gradient algorithm called Graph Proximal Policy Optimization (GPPO), which integrates GNNs into both the actor and critic networks. By incorporating both node and edge features, the GDRL enhances feature extraction from the RAN's nodes and links, providing richer observational data for decision-making and evaluation. This, in turn, enables more accurate and effective decision outcomes. In addition, we formulate the problem as a mixed-integer nonlinear programming model aimed at minimizing the number of active computational nodes while maximizing the centralization level of the virtualized RAN (vRAN). We evaluate the GDRL across different RAN scenarios with varying node configurations. The results demonstrate that our approach achieves superior network centralization and outperforms several existing methods in overall performance.

关键词： network function placement functional split radio access network deep reinforcement learning graph neural networks proximal policy optimization

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network function placement for NFV Chaining in Packet/Optical Datacenters

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JOURNAL OF LIGHTWAVE TECHNOLOGY 2015年第8期33卷 1565-1570页

作者： Xia, Ming Shirazipour, Meral Zhang, Ying Green, Howard Takacs, Attila Ericsson Res Silicon Valley San Jose CA 95134 USA HP Labs Palo Alto CA USA

In an operator's datacenter, optical technologies can be employed to perform network function (NF) chaining for larger aggregated flows in parallel with the conventional packet-based fine-grained traffic steering schemes. When network function virtualization (NFV) is enabled, virtualized NFs (vNF) can be placed when and where needed. In this study, we identify the possibility of minimizing the expensive optical/electronic/optical (O/E/O) conversions for NFV chaining in packet/optical datacenters, which is introduced by the on-demand placement of vNFs. When the vNFs of the same NF chain are properly grouped into fewer pods, traffic flows can avoid unnecessary traversals in the optical domain. We formulate the problem of optimal vNF placement in binary integer programming (BIP), and propose an alternative efficient heuristic algorithm to solve this problem. Evaluation results show that our algorithm can achieve near-optimal O/E/O conversions comparable to BIP. We also demonstrate the effectiveness of our algorithm under various scenarios, with comparison to a simple first-fit algorithm.

关键词： Datacenter network function placement network function virtualization optical service chaining

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network function placement for Service Chains with Server Maintenance Cost

Network Function Placement for Service Chains with Server Ma...

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IEEE Wireless Communications and networking Conference (IEEE WCNC)

作者： Tan, Zhuangyi Zhang, Jinbei Sun Yat Sen Univ Sch Elect & Commun Engn Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781728151786

network function virtualization (NFV) is a technique of building modern network architecture that can decouple network functions from proprietary equipment and thus increase the flexibility of network services deployment while reducing the total cost significantly. In the NFV scheme, network functions are placed on generic servers over the network. When a network service is requested, it will be implemented by chaining several Virtual network functions (VNFs) placed on servers to form a Service function Chain (SFC). The deployment of SFC faces an unprecedented challenge: when several network services are requested, which servers should be chosen to form service function chains while minimizing the total cost? Many existing optimization models consider the feasibility of placing the SFCs or minimizing the resource consumed by the VNFs. However, activate and maintain a server to hold VNFs also consume a huge amount of energy, and it's possible to lower the total energy cost by carefully arrange the servers with low maintenance cost. Therefore, in this paper, to investigate the network function placement for service chains with server maintenance cost, we propose a heuristic algorithm, which firstly constructs a server set that may accommodate all service chains with low server maintenance costs. Then it formulates linear programming to find the schemes of chaining the VNFs (also called placement configurations) with minimum communication cost in the server set and obtain its optimal fractional solutions. Eventually, we perform a rounding scheme to achieve integer solutions that outperform the greedy scheme in many evaluations.

关键词： Heuristic Algorithm network function placement Server Maintenance Cost

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A fix-and-optimize approach for efficient and large scale virtual network function placement and chaining

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COMPUTER COMMUNICATIONS 2017年第Apr.1期102卷 67-77页

作者： Luizelli, Marcelo Caggiani da Costa Cordeiro, Weverton Luis Buriol, Luciana S. Gaspary, Luciano Paschoal Univ Fed Rio Grande do Sul Inst Informat Av Bento Gongalves 9500 BR-91501970 Porto Alegre RS Brazil

network function Virtualization (NFV) is a novel concept that is reshaping the middlebox arena, shifting network functions (e.g. firewall, gateways, proxies) from specialized hardware appliances to software images running on commodity hardware. This concept has potential to make network function provision and operation more flexible and cost-effective, paramount in a world where deployed middleboxes may easily reach the order of hundreds. In spite of recent research activity in the field, little has been done towards efficient and scalable placement & chaining of virtual network functions (VNFs) - a key feature for the effective success of NFV. More specifically, existing strategies have either neglected the chaining aspect of NFV, focusing on efficient placement only, or failed to scale to hundreds of network functions. In this paper, we approach VNF placement and chaining as an optimization problem, and propose a fix-and-optimize-based heuristic algorithm for tackling it. Our algorithm incorporates a Variable Neighborhood Search (VNS) meta-heuristic, for efficiently exploring the placement and chaining solution space. The goal is to minimize required resource allocation, while meeting network flow requirements and constraints. We provide evidence that our algorithm is able to find feasible, high quality solutions efficiently, even in scenarios scaling to hundreds of VNFs. (C) 2016 Elsevier B.V. All rights reserved.

关键词： NFV network function placement Service function Chaining Optimization Fix-and-optimize Variable Neighborhood Search

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An online distributed approach to network function placement in NFV-enabled networks

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SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES 2021年第1期46卷 1-18页

作者： Anbiah, Anix Sivalingam, Krishna M. Indian Inst Technol Madras Dept Comp Sci & Engn Chennai Tamil Nadu India

network function placement (NFP) involves placing virtual network functions (VNFs) on the nodes of a network such that the data that flow through the network are processed by a chain of service functions along their path from source to destination. There are three aspects to this problem: (i) routing the flows efficiently through the network, (ii) placement of the VNFs on the nodes and (iii) steering each flow through a chain of VNFs, known as the service function chain (SFC). Routing must attempt to find "optimal" paths through the network (for e.g., shortest paths), possibly subject to constraints such as path latency and link bandwidth. The VNFs consume resources on the nodes where they are placed and are constrained by the capacity of the nodes. Steering must ensure that each flow has along its path a sequence of VNFs, likely in a certain order. One way to specify this problem is to define a multi-commodity flow problem with additional constraints based on the steering and placement requirements. Simultaneously solving all three aspects of this problem, trying to optimize various parameters and within the various constraints, is a hard problem, with even a simplified version shown to be NP-complete in this paper. Attempting to optimally solve this problem in real time while flows are getting provisioned and de-provisioned in parallel is an intractable problem, especially in large networks. Hence various types of heuristics have been used to solve this problem. In this paper we introduce a distributed, online solution that employs a message-passing protocol for nodes to negotiate the placement of the VNFs, with the minimization of the number of VNF instances being the primary objective. We compare the performance of the solution to that of the theoretically optimal solution and other proposed heuristics on both the Fat-tree topology and the BCube topology. The results show that this solution performs better than other heuristics. The average ratio of the result o

关键词： Software-Defined networks network function Virtualization network function placement distributed

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Funplace: A Protocol for network function placement 42

Funplace: A Protocol for Network Function Placement

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IEEE 42nd Conference on Local Computer networks (IEEE LCN)

作者： Anbiah, Anix Sivalingam, Krishna M. Indian Inst Technol Madras Dept Comp Sci & Engn Madras Tamil Nadu India

ISBN: (纸本)9781509065226

The network function placement (NFP) problem involves placing Virtual network functions (VNFs) in a network in order to meet the Service function Chain (SFC) requirements of the flows through the network. Simultaneously, the usage of network resources by the VNF instances must be optimized. Prior work primarily treated this as a constraint satisfaction problem, using linear programming to find optimal solutions. In contrast, this paper presents a distributed approach, based on a message-passing network protocol. This approach allows network nodes to negotiate the placement of VNF instances. A discreteevent simulation of the protocol is used to demonstrate it as a viable technique. A non-linearly constrained optimization (NCO) formulation is used to find optimal solutions for comparison and it is shown that the protocol yields nearly optimal solutions.

关键词： network function placement Virtual network functions Distributed Algorithm network Protocol

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Virtual network function placement Method for Evolving network Slices based on Salience 17

Virtual Network Function Placement Method for Evolving Netwo...

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IEEE 17th Annual Consumer Communications and networking Conference (CCNC)

作者： Hirayama, Takahiro Jibiki, Masahiro Kafle, Ved P. Natl Inst Informat & Commun Technol NICT Tokyo Japan

ISBN: (数字)9781728138930

ISBN: (纸本)9781728138930

network function virtualization (NFV) technology enables us to deploy a distinct network slice composed of various virtualized network functions (VNFs) required for a given service, such as video on demand (VoD) and Internet-of-things (IoT). As a result, application service providers (ASPs) can easily deploy and provide their services to end users (EUs) by leasing resources formed as network slices. However, as the user population or the network traffic volume fluctuates, the capacity of network slices has to be adjusted dynamically. It requires to take decision about placing NFs in appropriate locations so that the quality of services (QoS), such as transmission or processing latency is guaranteed while optimally utilizing the reserved resources. One can address the above challenge by solving an optimization problem such as integer linear programming. However, the optimization problem takes much time to solve. In this paper, we propose a network function placement algorithm based on salience, which is one of characteristic metrics of links in graphs. Our objectives are two folds: keeping the slice reconstruction cost low, and avoiding the cases of QoS degradation. The simulation results show that our scheme performs equally well for different sizes of slices (i.e., the number of EUs). When slices are reconstructed with our scheme in a 200-node network, we found that the network reconfiguration costs are low and almost the same value for various sizes of slices.

关键词： network function placement network function Virtualization (NFV) network Slicing Horizontal Scaling

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Service and network function placement in the edge-cloud continuum

Service and network function placement in the edge-cloud con...

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IEEE Conference on Standards for Communications and networking (IEEE CSCN)

作者： Tsolkas, Dimitris Charsmiadis, Anastastios-Stavros Xenakis, Dionysis Merakos, Lazaros NKUA Dept Informat & Telecommun Athens Greece FOGUS Innovat Serv PC Kaisariani Greece

ISBN: (纸本)9781665476218

The virtualization and containerization technologies have paved the way towards a flexible and fully programmable service provisioning chain over mobile telecommunication infrastructures. On top of those technologies the network slicing concept has emerged;a concept that enables the installation and migration of service and network functions on a compute fabric that spans from the central cloud to distributed far-edge hosts. In this context, the efficient placement of service and network functions in the hosts of the continuum is an open and challenging problem. We formulate this problem as a scheduling process and we analyze its optimal performance through the integer linear programming toolkit. The study revealed interesting insights regarding the impact of sequence constraints (i.e., some functions should be allocated according to a specific order) and host-continuity constraints (i.e., some functions should be allocated in the same cloud host with others) to the overall efficiency of the scheduling.

关键词： network function placement network slicing edge-cloud continuum Integer linear programming

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A network operator-biased approach for multi-service network function placement in a 5G network slicing architecture

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COMPUTER networkS 2021年 201卷 108598-108598页

作者： Shinde, Swapnil Sadashiv Marabissi, Dania Tarchi, Daniele Univ Bologna Dept Elect Elect & Informat Engn Guglielmo Marcon Viale Risorgimento 2 I-40136 Bologna Italy Univ Florence Dept Informat Engn Via Santa Marta3 I-50139 Florence Italy

The 5G communication standard is characterized by an increased softwarization, allowing a higher flexibility able to cope with different requirements and services. In particular, network function Virtualization (NFV) is a recently introduced technology that enables a software implementation of different network functions exploiting virtualization techniques, hence, enabling their flexible deployment upon system requirements. Boosted by NFV, the concept of network slicing is gaining great attention in 5G networks. The idea is that physical communication and computing resources are sliced in multiple end-to-end logical networks, each one tailored to best support a specific service. The advantages of NFV, in the network slicing context, are even more evident in distributed computing environments, such as the edge-to-cloud continuum, recently introduced for enabling a flexible deployment of multiple functions. In particular, thanks to the introduction of cloud-native technologies, based on the usage of containerization and microservice technologies, the virtual network functions (VNFs) deployment and their orchestration is an easy operation, allowing the on-the-fly network configuration. Gaining from the NFV, network Slicing and Edge-to-Cloud continuum paradigms, we propose a new network function allocation problem for multi-service 5G networks, able to deploy network functions on a distributed computing environment depending on the service requests. The proposed approach jointly considers Radio Access network (RAN) and Core network (CN) functions and, differently from other approaches, introduces an option able to bias the function placement depending on the service requirements, allowing a fast-and-easy operator-side deployment of the network functions. We propose to solve the problem through a Genetic Algorithm able to approach the optimal solution but with reduced complexity and execution time. The performance is compared with two other heuristic algorithms and with

关键词： 5G network slicing Edge Computing network function placement Genetic Algorithms

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Prune and Plant: Efficient placement and Parallelism of Virtual network functions

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IEEE TRANSACTIONS ON COMPUTERS 2020年第6期69卷 800-811页

作者： Bao, Wei Yuan, Dong Zhou, Bing Bing Zomaya, Albert Y. Univ Sydney Sch Comp Sci Sydney NSW 2006 Australia Univ Sydney Sch Elect & Informat Engn Sydney NSW 2006 Australia

network function virtualization (NFV) is a promising solution to realize a variety of network services. By definition, virtual network functions (VNFs) are chained together to realize different services. However, chaining is not an ideal solution as service latency grows linearly with respect to the length of the chain. Motivated by the fact that many VNFs can be parallelized, we investigate parallelism of VNFs for acceleration. The dependency of the VNFs is characterized by a directed acyclic graph (DAG). We aim to deploy the VNFs in the right place and process them in parallel without violating the DAG, to minimize the overall delay. However, directly solving the delay minimization problem is NP-hard, and it may also introduce a large number of duplicated packets to burden the system. To deal with these issues, we propose the Prune and Plant (P&P) scheme with polynomial computational complexity, to reduce the overall delay while limiting the number of duplicated packets. P&P comprises two stages: in the Prune stage, we prune the original DAG into a series-parallel graph (SP-graph), which eliminates NP-hardness while maintaining parallelism of VNFs. In the Plant stage, we find the optimal placement for the VNFs with respect to the SP-graph. By both simulation and prototyping, we demonstrate that P&P significantly outperforms benchmark schemes.

关键词： network function virtualization network function placement delay minimization parallelism

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