Relevant bibliographies by topics / Reconfiguration des VNFs

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  1. Journal articles
  2. Dissertations / Theses
  3. Conference papers

Academic literature on the topic 'Reconfiguration des VNFs'

Author: Grafiati
Published: 3 April 2023
Last updated: 19 July 2025

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Journal articles on the topic "Reconfiguration des VNFs"

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Guo, Shuang, Liang Liu, Tengxiang Jing, and Huan Liu. "SFC active reconfiguration based on user mobility and resource demand prediction in dynamic IoT-MEC networks." PLOS ONE 19, no. 8 (2024): e0306777. http://dx.doi.org/10.1371/journal.pone.0306777.

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To achieve secure, reliable, and scalable traffic delivery, request streams in mobile Internet of Things (IoT) networks supporting Multi-access Edge Computing (MEC) typically need to pass through a service function chain (SFC) consisting of an ordered series of Virtual Network Functions (VNFs), and then arrive at the target application in the MEC for processing. The high mobility of users and the real-time variability of network traffic in IoT-MEC networks lead to constant changes in the network state, which results in a mismatch between the performance requirements of the currently deployed SFCs and the allocated resources. Meanwhile, there are usually multiple instances of the same VNF in the network, and proactively reconfiguring the deployed SFCs based on the network state changes to ensure high quality of service in the network is a great challenge. In this paper, we study the SFC Reconfiguration Strategy (SFC-RS) based on user mobility and resource demand prediction in IoT MEC networks, aiming to minimize the end-to-end delay and reconfiguration cost of SFCs. First, we model SFC-RS as Integer Linear Programming (ILP). Then, a user trajectory prediction model based on codec movement with attention mechanism and a VNF resource demand prediction model based on the Long Short-Term Memory (LSTM) network are designed to accurately predict user trajectories and node computational and storage resources, respectively. Based on the prediction results, a Prediction-based SFV Active Reconfiguration (PSAR) algorithm is proposed to achieve seamless SFC migration and routing update before the user experience quality degrades, ensuring network consistency and high quality service. Simulation results show that PSAR provides 51.28%, 28.60%, 21.75%, and 16.80% performance improvement over the existing TSRFCM, DDQ, OSA, and DPSM algorithms in terms of end-to-end delay reduction, and 33.32%, 18.94%, 67.42%, and 60.61% performance optimization in terms of reconfiguration cost reduction.
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Liu, Bei, Shuting Long, and Xin Su. "Knowledge-Assisted Actor Critic Proximal Policy Optimization-Based Service Function Chain Reconfiguration Algorithm for 6G IoT Scenario." Entropy 26, no. 10 (2024): 820. http://dx.doi.org/10.3390/e26100820.

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Future 6G networks will inherit and develop Network Function Virtualization (NFV) architecture. With the NFV-enabled network architecture, it becomes possible to establish different virtual networks within the same infrastructure, create different Virtual Network Functions (VNFs) in different virtual networks, and form Service Function Chains (SFCs) that meet different service requirements through the orderly combination of VNFs. These SFCs can be deployed to physical entities as needed to provide network functions that support different services. To meet the highly dynamic service requirements in the future 6G Internet of Things (IoT) scenario, the highly flexible and efficient SFC reconfiguration algorithm is the key research direction. Deep-learning-based algorithms have shown their advantages in solving this type of dynamic optimization problem. Considering that the efficiency of the traditional Actor Critic (AC) algorithm is limited, the policy does not directly participate in the value function update. In this paper, we use the Proximal Policy Optimization (PPO) clip function to restrict the difference between the new policy and the old policy, to ensure the stability of the updating process. We combine PPO with AC, and further bring the historical decision information as the network knowledge to offer better initial policies, to accelerate the training speed. We also propose the Knowledge = Assisted Actor Critic Proximal Policy Optimization (KA-ACPPO)-based SFC reconfiguration algorithm to ensure the Quality of Service (QoS) of end-to-end services. Simulation results show that the proposed KA-ACPPO algorithm can effectively reduce computing cost and power consumption.
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Qiao, Wenxin, Hao Lu, Yu Lu, Lijie Meng, and Yicen Liu. "A Dynamic Service Reconfiguration Method for Satellite–Terrestrial Integrated Networks." Future Internet 13, no. 10 (2021): 260. http://dx.doi.org/10.3390/fi13100260.

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Satellite–terrestrial integrated networks (STINs) are regarded as a promising solution to meeting the demands of global high-speed seamless network access in the future. Software-defined networking and network function virtualization (SDN/NFV) are two complementary technologies that can be used to ensure that the heterogeneous resources in STINs can be easily managed and deployed. Considering the dual mobility of satellites and ubiquitous users, along with the dynamic requirements of user requests and network resource states, it is challenging to maintain service continuity and high QoE performance in STINs. Thus, we investigate the service migration and reconfiguration scheme, which are of great significance to the guarantee of continuous service provisioning. Specifically, this paper proposes a dynamic service reconfiguration method that can support flexible service configurations on integrated networks, including LEO satellites and ground nodes. We first model the migration cost as an extra delay incurred by service migration and reconfiguration and then formulate the selection processes of the location and migration paths of virtual network functions (VNFs) as an integer linear programming (ILP) optimization problem. Then, we propose a fuzzy logic and quantum genetic algorithm (FQGA) to obtain an approximate optimal solution that can accelerate the solving process efficiently with the benefits of the high-performance computing capacity of QGA. The simulation results validate the effectiveness and improved performance of the scheme proposed in this paper.
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Liu, Yanyang, Jing Ran, Hefei Hu, and Bihua Tang. "Energy-Efficient Virtual Network Function Reconfiguration Strategy Based on Short-Term Resources Requirement Prediction." Electronics 10, no. 18 (2021): 2287. http://dx.doi.org/10.3390/electronics10182287.

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In Network Function Virtualization, the resource demand of the network service evolves with the change of network traffic. VNF dynamic migration has become an effective method to improve network performance. However, for the time-varying resource demand, how to minimize the long-term energy consumption of the network while guaranteeing the Service Level Agreement (SLA) is the key issue that lacks previous research. To tackle this dilemma, this paper proposes an energy-efficient reconfiguration algorithm for VNF based on short-term resource requirement prediction (RP-EDM). Our algorithm uses LSTM to predict VNF resource requirements in advance to eliminate the lag of dynamic migration and determines the timing of migration. RP-EDM eliminates SLA violations by performing VNF separation on potentially overloaded servers and consolidates low-load servers timely to save energy. Meanwhile, we consider the power consumption of servers when booting up, which is existing objectively, to avoid switching on/off the server frequently. The simulation results suggest that RP-EDM has a good performance and stability under machine learning models with different accuracy. Moreover, our algorithm increases the total service traffic by about 15% while ensuring a low SLA interruption rate. The total energy cost is reduced by more than 20% compared with the existing algorithms.
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Biallach, Hanane, Mustapha Bouhtou, Kristina Kumbria, Dritan Nace, and Artur Tomaszewski. "Virtual network function reconfiguration in 5G networks: An optimization perspective." Networks, February 8, 2024. http://dx.doi.org/10.1002/net.22212.

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AbstractOne of the major challenges in managing 5G networks is the reconfiguration of network slices. The task covers in particular reconfiguration and relocation of virtual network functions (VNFs) so as to match the service requirements of the slices and the availability of resources of the data centers. In this article, we study in deep the problem of optimal VNFs reconfiguration analyzing a number of its variants. We define two exact, compact integer linear programming formulations of the VNFs reconfiguration problem, and derive two approximate solution algorithms, one of them based on the column generation method. Numerical tests and comparisons illustrate the performance of the algorithms and the quality of the provided solutions.
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Amiri, Esmaeil, Ning Wang, Mohammad Shojafar, Mutasem Q. Hamdan, Chuan Heng Foh, and Rahim Tafazolli. "Deep Reinforcement Learning for Robust VNF Reconfigurations in O-RAN." IEEE Transactions on Network and Service Management, 2023, 1. http://dx.doi.org/10.1109/tnsm.2023.3316074.

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Cisneros, Josue Castaneda, Saul E. Pomares Hernandez, Julio Cesar Perez Sansalvador, Lil M. Rodriguez Henriquez, Sami Yangui, and Khalil Drira. "Coordination-free Multi-domain NFV Orchestration for Consistent VNF Forwarding Graph Reconfiguration." IEEE Transactions on Network and Service Management, 2022, 1. http://dx.doi.org/10.1109/tnsm.2022.3192328.

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Li, Tingyu, and Zuqing Zhu. "QoS-aware Management Reconfiguration of vNF Service Trees with Heterogeneous NFV Platforms." IEEE Transactions on Network and Service Management, 2022, 1. http://dx.doi.org/10.1109/tnsm.2022.3220229.

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Castañeda, Josué, Saul E. Pomares Hernández, Sami Yangui, Julio C. Pérez Sansalvador, Lil, M. Rodríguez Henríquez, and Khalil Drira. "VNF-based network service consistent reconfiguration in multi-domain federations: A distributed approach." Journal of Network and Computer Applications, September 2021, 103226. http://dx.doi.org/10.1016/j.jnca.2021.103226.

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Roberto, Bruschi, Davoli Franco, Lago Paolo, and Frances Pajo Jane. "A Multi-Clustering Approach to Scale Distributed Tenant Networks for Mobile Edge Computing." January 23, 2019. https://doi.org/10.1109/JSAC.2019.2894236.

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Fifth generation (5G) mobile networks will lead to a deep integration between networks and applications. Through novel paradigms like network functions virtualization and edge computing, the new classes of heterogeneous application services will be enabled to run close to the mobile end-user devices with zero-perceived latency and fully-cognitive dynamic reconfiguration capabilities. Such “vertical” applications exhibit diverse performance/scalability requirements, and will rely on highly distributed, extremely virtualized, multi-tenant, and software-defined infrastructures. In such a context, handling the required operations in a scalable and dynamic fashion will be of paramount importance. A specific aspect, addressed by software-defined networking (SDN), regards the provision of suitable communication channels, once resource allocation mechanisms have performed the most efficient deployment of virtual network function instances, and VNF chaining needs to be implemented to enable network services. In this respect, this paper introduces the multi-cluster overlay (MCO) network paradigm: a tunnel-less SDN scheme for scalable realization of virtual tenant networks across the 5G distributed infrastructure, able to support (bulk) migrations of software instances among geo-distributed computing resources in a seamless and effective fashion. The numerical simulation and experimental results show that the MCO achieves up to over one order of magnitude smaller number of forwarding rules than the other state-of-the-art SDN mechanisms, while also assuring high performance during reconfiguration operations.
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Dissertations / Theses on the topic "Reconfiguration des VNFs"

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Biallach, Hanane. "Optimization of VNF reconfiguration problem for 5G network slicing." Electronic Thesis or Diss., Compiègne, 2022. http://www.theses.fr/2022COMP2707.

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Ces dernières années, en raison de la croissance sans précédent du nombre d'appareils connectés et de données mobiles, et des développements continus des technologies pour répondre à cette énorme demande de données, le réseau de cinquième génération (5G) a émergé. La future architecture 5G sera essentiellement basée sur le Network Slicing (NS), qui permet de fournir une approche flexible pour réaliser la vision 5G. Grâce au concept émergent de virtualisation des fonctions réseau (NFV), les fonctions réseau sont découplées des matériels physiques dédiés et réalisées sous forme de logiciel. Cela offre plus de flexibilité et d'agilité dans les opérations commerciales. Malgré les avantages qu'il apporte, NFV soulève quelques défis techniques, le problème de reconfiguration étant l'un d'entre eux. Ce problème, qui est NP-difficile, consiste à réaffecter les fonctions de réseau virtuel (VNFs) pour s'adapter aux changements du réseau, en transformant l'état courant des services déployés, on peut illustrer cela par la migration des machines virtuelles (VM) qui hébergent les VNF, à un autre état qui répond aux objectives des opérateurs. Cette thèse de doctorat étudie comment reconfigurer les VNFs en les migrant vers un état optimal qui pourrait être calculé en avance ou inconnu. Dans cette thèse, nous avons étudié les deux cas en minimisant la durée d'interruption de service et la durée de migration des VNFs. Nous avons proposé des méthodes exactes et approchées. Parmi les méthodes exactes, nous citons deux modèles PLNE. Nous avons également proposé deux approches heuristiques, l'une basée sur la génération de colonnes et la deuxième utilisant la notion de “feedback arc set". L'objectif global de ce travail est donc de définir et d'étudier le problème de reconfiguration des VNFs dans le contexte du 5G network slicing, et de proposer des modèles mathématiques et des algorithmes efficaces pour résoudre les problèmes d'optimisation sous-jacents<br>In recent years, because of the unprecedented growth in the number of connected devices and mobile data, and the ongoing developments in technologies to address this enormous data demand, the fifth generation (5G) network has emerged. The forthcoming 5G architecture will be essentially based on Network Slicing (NS), which enables provide a flexible approach to realize the 5G vision. Thanks to the emerging Network Function Virtualization (NFV) concept, the network functions are decoupled from dedicated hardware devices and realized in the form of software. This offers more flexibility and agility in business operations. Despite the advantages it brings, NFV raises some technical challenges, the reconfiguration problem is one of them. This problem, which is NP-Hard, consists in reallocating the Virtual Network Functions (VNFs) to fit the network changes, by transforming the current state of deployed services, e.g., the current placement of Virtual Machines (VM) that host VNFs, to another state that updates providers’ objectives. This PhD thesis investigates how to reconfigure the VNFs by migrating them to an optimal state that could be computed in advance or free placement. In this thesis, we studied both cases while minimizing the service interruption duration and the VNF migration duration. We have proposed exact and approximate methods. Among the exact methods, we cite two ILP models. We also proposed two heuristic approaches, one based on column generation and the second using the concept of “arc set feedback”. The overall objective of this work is therefore to define and study the problem of VNF reconfiguration problem in the context of 5G network slicing, and propose mathematical models and efficient algorithms to solve the underlying optimization problems
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Conference papers on the topic "Reconfiguration des VNFs"

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Kumbria, Kristina, Denis Demko, Dritan Nace, Artur Tomaszewski, Mustapha Bouhtou, and Hanane Biallach. "VNFs reconfiguration in 5G networks." In 2022 12th International Workshop on Resilient Networks Design and Modeling (RNDM). IEEE, 2022. http://dx.doi.org/10.1109/rndm55901.2022.9927655.

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Deric, Nemanja, Amir Varasteh, Arsany Basta, et al. "Coupling VNF Orchestration and SDN Virtual Network Reconfiguration." In 2019 International Conference on Networked Systems (NetSys). IEEE, 2019. http://dx.doi.org/10.1109/netsys.2019.8854520.

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Cisneros, Josue Castaneda, Sami Yangui, Saul E. Pomares Hernandez, Julio Cesar Perez Sansalvador, Lil M. Rodriguez Henriquez, and Khalil Drira. "Towards Consistent VNF Forwarding Graph Reconfiguration in Multi-domain Environments." In 2021 IEEE 14th International Conference on Cloud Computing (CLOUD). IEEE, 2021. http://dx.doi.org/10.1109/cloud53861.2021.00049.

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Li, Tingyu, and Zuqing Zhu. "Leveraging Heterogeneous NFV Platforms for QoS-aware Reconfiguration of vNF Service Trees." In 2022 20th International Conference on Optical Communications and Networks (ICOCN). IEEE, 2022. http://dx.doi.org/10.1109/icocn55511.2022.9901177.

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Maier, Guido, Leila Askari, Sebastian Troia, Ligia Maria Moreira Zorello, Francesco Musumeci, and Massimo Tornatore. "Reconfiguration of VNF Placement in an Optical Metro Network by a Modular Planning Tool." In Optical Fiber Communication Conference. OSA, 2020. http://dx.doi.org/10.1364/ofc.2020.w2a.27.

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