Literatura académica sobre el tema "Network slicing in 5G"
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Artículos de revistas sobre el tema "Network slicing in 5G"
Gao, Shujuan, Ruyan Lin, Yulong Fu, Hui Li y Jin Cao. "Security Threats, Requirements and Recommendations on Creating 5G Network Slicing System: A Survey". Electronics 13, n.º 10 (10 de mayo de 2024): 1860. http://dx.doi.org/10.3390/electronics13101860.
Texto completoMakhija, Deven. "5G Communication Systems: Network Slicing and Virtual Private Network Architecture". ITM Web of Conferences 54 (2023): 02001. http://dx.doi.org/10.1051/itmconf/20235402001.
Texto completoMunir, Rizwan, Yifei Wei, Chao Ma y Bizhu Yang. "Dynamically Resource Allocation in Beyond 5G (B5G) Network RAN Slicing Using Deep Deterministic Policy Gradient". Wireless Communications and Mobile Computing 2022 (21 de diciembre de 2022): 1–13. http://dx.doi.org/10.1155/2022/9958786.
Texto completoJia, Qingmin, RenChao Xie, Tao Huang, Jiang Liu y Yunjie Liu. "Caching Resource Sharing for Network Slicing in 5G Core Network". Journal of Organizational and End User Computing 31, n.º 4 (octubre de 2019): 1–18. http://dx.doi.org/10.4018/joeuc.2019100101.
Texto completoWong, Stan, Bin Han y Hans D. Schotten. "5G Network Slice Isolation". Network 2, n.º 1 (8 de marzo de 2022): 153–67. http://dx.doi.org/10.3390/network2010011.
Texto completoDayot, Ralph Voltaire J., In-Ho Ra y Hyung-Jin Kim. "A Deep Contextual Bandit-Based End-to-End Slice Provisioning Approach for Efficient Allocation of 5G Network Resources". Network 2, n.º 3 (23 de junio de 2022): 370–88. http://dx.doi.org/10.3390/network2030023.
Texto completoMAKSYMYUK, Taras, Volodymyr ANDRUSHCHAK, Stepan DUMYCH, Bohdan SHUBYN, Gabriel BUGÁR y Juraj GAZDA. "BLOCKCHAIN-BASED NETWORK FUNCTIONS VIRTUALIZATION FOR 5G NETWORK SLICING". Acta Electrotechnica et Informatica 20, n.º 4 (21 de enero de 2021): 54–59. http://dx.doi.org/10.15546/aeei-2020-0026.
Texto completoKannan, Yamini. "Network Slicing in 5G Systems: Challenges, Opportunities and Implementation Approaches". International Journal of Innovative Research in Information Security 10, n.º 02 (24 de febrero de 2024): 51–56. http://dx.doi.org/10.26562/ijiris.2023.v1002.02.
Texto completoDangi, Ramraj, Akshay Jadhav, Gaurav Choudhary, Nicola Dragoni, Manas Kumar Mishra y Praveen Lalwani. "ML-Based 5G Network Slicing Security: A Comprehensive Survey". Future Internet 14, n.º 4 (8 de abril de 2022): 116. http://dx.doi.org/10.3390/fi14040116.
Texto completoSohaib, Rana Muhammad, Oluwakayode Onireti, Yusuf Sambo y Muhammad Ali Imran. "Network Slicing for Beyond 5G Systems: An Overview of the Smart Port Use Case". Electronics 10, n.º 9 (5 de mayo de 2021): 1090. http://dx.doi.org/10.3390/electronics10091090.
Texto completoTesis sobre el tema "Network slicing in 5G"
Bakri, Sihem. "Towards enforcing network slicing in 5G networks". Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS067.
Texto completoThe current architecture “one size fits all” of 4G network cannot support the next-generation 5G heterogeneous services criteria. Therefore, research around 5G aims to provide more adequate architectures and mechanisms to deal with this purpose. The 5G architecture is envisioned to accommodate the diverse and conflicting demands of services in terms of latency, bandwidth, and reliability, which cannot be sustained by the same network infrastructure. In this context, network slicing provided by network virtualization allows the infrastructure to be divided into different slices. Each slice is tailored to meet specific service requirements allowing different services (such as automotive, Internet of Things, etc.) to be provided by different network slice instances. Each of these instances consists of a set of virtual network functions that run on the same infrastructure with specially adapted orchestration. Three main service classes of network slicing have been defined by the researchers as follows: Enhanced Mobile Broadband (eMBB), massive Machine Type Communication (mMTC), and ultra-Reliable and Low-Latency Communication (uRLLC). One of the main challenges when it comes to deploying Network Slices is slicing the Radio Access Network (RAN). Indeed, managing RAN resources and sharing them among Network Slices is an increasingly difficult task, which needs to be properly designed. This thesis proposes solutions that aim to improve network performance, and introduce flexibility and greater utilization of network resources by accurately and dynamically provisioning the activated network slices with the appropriate amounts of resources to meet their diverse requirements
Suárez, Trujillo Luis Carlos. "Securing network slices in 5th generation mobile networks". Thesis, Brest, 2020. http://www.theses.fr/2020BRES0050.
Texto completoNetwork slicing is a cornerstone in the conception and deployment of enriched communication services for the new use cases envisioned and supported by the new 5G architecture.This document makes emphasis on the challenge of the network slicing isolation and security management according to policy. First, a novel access control model was created, that secures the interactions between network functions that reside inside the 5G system. Then, the management of the interactions between network slices was addressed. We coin the concept of network slice chains, which are conceived after security constraint validation according to policy. Lastly, a method to quantify isolation was developed, permitting to find out how well isolated a communication service is, which is offered via network slices. This enables network operators and customers to measure the isolation level and improve the configuration of the network slices so the isolation level can be enhanced. These components establish a solid framework that contributes to secure, vertically, the communication services of a 5G network and assess how secure they are with respect to their interactions and isolation
Chang, Chia-Yu. "Cloudification and Slicing in 5G Radio Access Network". Electronic Thesis or Diss., Sorbonne université, 2018. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2018SORUS293.pdf.
Texto completoOver the past few decades, the continuing growth of network statistics requires a constantly evolving technology. Therefore, a natural question arises in our minds: what will 5G be? To answer this question, the 5G architecture must be designed with a certain level of flexibility through the integration of softwarization and virtualization principles. Therefore, we can see that 5G will provide a paradigm shift beyond radio access technology in order to establish an agile and sophisticated communication system. The network can be used efficiently and independently by creating multiple logically separated spaces, called network slices. In addition, each logical network can deploy its network functions in a flexible cloud environment. To this end, the goal of this thesis is to study these two techniques: (a) Cloud-RAN and (b) RAN splitting. In the first part, our focus is on the C-RAN concept, in which monolithic base stations are replaced by (1) distributed radio elements and (2) centralized pools for baseband processing units. The C-RAN notion is still confronted with stringent capacity and latency requirements of the fronthaul interface that connects the distributed remote radio unit to the centralized baseband processing unit. In the second part, we focus on RAN cutting not only to allow different levels of isolation and sharing at each slice of network, but also to customize the control plane, user plane and control logic. Therefore, we provide a flexible runtime environment for the "RAN Runtime" slicing system to host service instances on each of the underlying RAN modules
Biallach, Hanane. "Optimization of VNF reconfiguration problem for 5G network slicing". Electronic Thesis or Diss., Compiègne, 2022. http://www.theses.fr/2022COMP2707.
Texto completoIn 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
Motyčka, Jan. "Implementace mechanismů zajišťujících “RAN Slicing” v simulačním nástroji Network Simulator 3". Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442360.
Texto completoSid-Otmane, Jonathan. "A study of data consistency constraints in 5G, applied to limiting resource usage in network slices". Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS537.
Texto completoThe 5G network specification requires ACID properties (Atomicity, Consistency, Isolation, Durability) for its distributed database. According to the CAP theorem, these properties are incompatible with high availability for a geo-distributed system. Since availability is an obligation for mobile networks, this contradiction challenges the specification. Our thesis focus on a study of the usage of data in the network that allow us to extract weaker consistency properties that are still sufficient to maintain the correctness of the data. In the case a Network Slicing, an innovation of the 5G network, we propose to study further the enforcement of one of these properties, through the example of the enforcement of a global limit on the resource usage of a slice. Slices are deployed over a potentially large are, and so is their data, which make the enforcement of a limit more challenging. We propose several algorithms placed at different points of the consistency spectrum and study their performance in a simulation of the 5G network
Matoussi, Salma. "User-Centric Slicing with Functional Splits in 5G Cloud-RAN". Electronic Thesis or Diss., Sorbonne université, 2021. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2021SORUS004.pdf.
Texto completo5G Radio Access Network (RAN) aims to evolve new technologies spanning the Cloud infrastructure, virtualization techniques and Software Defined Network capabilities. Advanced solutions are introduced to split the RAN functions between centralized and distributed locations to improve the RAN flexibility. However, one of the major concerns is to efficiently allocate RAN resources, while supporting heterogeneous 5G service requirements. In this thesis, we address the problematic of the user-centric RAN slice provisioning, within a Cloud RAN infrastructure enabling flexible functional splits. Our research aims to jointly meet the end users’ requirements, while minimizing the deployment cost. The problem is NP-hard. To overcome the great complexity involved, we propose a number of heuristic provisioning strategies and we tackle the problem on four stages. First, we propose a new implementation of a cost efficient C-RAN architecture, enabling on-demand deployment of RAN resources, denoted by AgilRAN. Second, we consider the network function placement sub-problem and propound a new scalable user-centric functional split selection strategy named SPLIT-HPSO. Third, we integrate the radio resource allocation scheme in the functional split selection optimization approach. To do so, we propose a new heuristic based on Swarm Particle Optimization and Dijkstra approaches, so called E2E-USA. In the fourth stage, we consider a deep learning based approach for user-centric RAN Slice Allocation scheme, so called DL-USA, to operate in real-time. The results obtained prove the efficiency of our proposed strategies
Maiorano, Picone Pasquale Carlo. "A QoS Controller Framework Compliant with the ETSI Network Function Virtualization Specification". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/10406/.
Texto completoBoutiba, Karim. "On enforcing Network Slicing in the new generation of Radio Access Networks". Electronic Thesis or Diss., Sorbonne université, 2024. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2024SORUS003.pdf.
Texto completoThe emerging 5G networks and beyond promise to support novel use cases such as immersive holographic communication, Internet of Skills, and 4D Interactive mapping [usecases]. These use cases require stringent requirements in terms of Quality of Service (QoS), such as low latency, high Downlink (DL)/Uplink (UL) throughput and low energy consumption. The 3rd Generation Partnership Project (3GPP) specifications introduced many features in 5G New Radio (NR) to improve the physical efficiency of 5G to meet the stringent and heterogeneous requirements of beyond 5G services. Among the key 5G NR features, we can mention the numerology, BandWidth Part (BWP), dynamic Time Duplex Division (TDD) and Connected-mode Discontinuous Reception (C-DRX). However, the specifications do not provide how to configure the next Generation Node B (gNB)/User Equipment (UE) in order to optimize the usage of the 5G NR features. We enforce the 5G NR features by applying Machine Learning (ML), particularly Deep Reinforcement Learning (DRL), to fill this gap. Indeed, Artificial Intelligence (AI)/ML is playing a vital role in communications and networking [1] thanks to its ability to provide a self-configuring and self-optimizing network.In this thesis, different solutions are proposed to enable intelligent configuration of the Radio Access Network (RAN). We divided the solutions into three different parts. The first part concerns RAN slicing leveraging numerology and BWPs. In contrast, the second part tackles dynamic TDD, and the last part goes through different RAN optimizations to support Ultra-Reliable and Low-Latency Communication (URLLC) services.In the first part, we propose two contributions. First, we introduce NRflex, a RAN slicing framework aligned with Open RAN (O-RAN) architecture. NRflex dynamically assigns BWPs to the running slices and their associated User Equipment (UE) to fulfill the slices' required QoS. Then, we model the RAN slicing problem as a Mixed-Integer Linear Programming (MILP) problem. To our best knowledge, this is the first MILP modeling of the radio resource management featuring network slicing, taking into account (i) Mixed-numerology, (ii) both latency and throughput requirements (iii) multiple slices attach per UE (iv) Inter-Numerology Interference (INI). After showing that solving the problem takes an exponential time, we consider a new approach in a polynomial time, which is highly required when scheduling radio resources. The new approach consists of formalizing this problem using a DRL-based solver.In the second part of this thesis, we propose a DRL-based solution to enable dynamic TDD in a single 5G NR cell. The solution is implemented in OAI and tested using real UEs. Then, we extend the solution by leveraging Multi-Agent Deep Reinforcement Learning (MADRL) to support multiple cells, considering cross-link interference between cells.In the last part, we propose three solutions to optimize the RAN to support URLLC services. First, we propose a two-step ML-based solution to predict Radio Link Failure (RLF). We combine Long Short-Term Memory (LSTM) and Support Vector Machine (SVM) to find the correlation between radio measurements and RLF. The RLF prediction model was trained with real data obtained from a 5G testbed. In the second contribution, we propose a DRL-based solution to reduce UL latency. Our solution dynamically allocates the future UL grant by learning from the dynamic traffic pattern. In the last contribution, we introduce a DRL-based solution to balance latency and energy consumption by jointly deriving the C-DRX parameters and the BWP configuration
Chagdali, Abdellatif. "Multi-connectivity and resource allocation for slices in 5G networks". Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPAST052.
Texto completoFuture mobile networks envision unprecedented innovation opportunities and disruptive use cases. As a matter of fact, the 5G and beyond networks' pledge to deliver mission-critical applications mandates a versatile, scalable, efficient, and cost-effective network capable of accommodating its resource allocation to meet the services' heterogeneous requirements. To face these challenges, network slicing has emerged as one of the fundamental concepts proposed to raise the 5G mobile networks' efficiency and provide the required plasticity. The idea is to provide resources for different vertical industries by building multiple end-to-end logical networks over a shared virtualized infrastructure. Each network slice is customized to deliver a specific service and adapts its architecture and radio access technologies.Precisely, applications such as industrial automation or vehicular communications pose stringent latency and reliability requirements on cellular networks. Given that the current mobile network cannot meet these requirements, ultra-reliable low-latency communications (URLLC) embodies a vital research topic that has gathered substantial momentum from academia and industrial alliances. To reach URLLC requirements, employing multi-connectivity (MC), i.e., exploiting multiple radio links as communication paths at once, is a promising approach.Therefore, the objective of the present manuscript is to investigate dynamic scheduling techniques, exploiting redundant coverage of users, guaranteed in numerous 5G radio access network scenarios. We first review the evolution of mobile networks and discuss various considerations for network slicing architecture and its impact on resource allocation design. Then, we use tools from queuing theory to model a system in which a set of URLLC users are connected simultaneously to two base stations having the same bandwidth; we refer to this scenario as the homogenous case. We introduce suitable scheduling policies and evaluate their respective performances by assessing their reliability. Next, we extend the homogenous case's results to a more general setting where the physical interfaces manage different bandwidths, referred to as the heterogeneous case. Finally, we merge the above elements to validate the choice of resource allocation schemes considering the deployed architecture
Libros sobre el tema "Network slicing in 5G"
Kazmi, S. M. Ahsan, Latif U. Khan, Nguyen H. Tran y Choong Seon Hong. Network Slicing for 5G and Beyond Networks. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16170-5.
Texto completoYe, Qiang y Weihua Zhuang. Intelligent Resource Management for Network Slicing in 5G and Beyond. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88666-0.
Texto completoShetty, Rajaneesh Sudhakar. 5G Mobile Core Network. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-6473-7.
Texto completoZhang, Ying. Network Function Virtualization: Concepts and Applicability in 5G Networks. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781119390633.
Texto completoDu, Zhiyong, Bin Jiang, Qihui Wu, Yuhua Xu y Kun Xu. Towards User-Centric Intelligent Network Selection in 5G Heterogeneous Wireless Networks. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1120-2.
Texto completoHong, Choong Seon, S. M. Ahsan Kazmi, Latif U. Khan y Nguyen H. Tran. Network Slicing for 5G and Beyond Networks. Springer, 2020.
Buscar texto completoHong, Choong Seon, S. M. Ahsan Kazmi, Latif U. Khan y Nguyen H. Tran. Network Slicing for 5G and Beyond Networks. Springer, 2019.
Buscar texto completoZhang, Lei, Arman Farhang, Gang Feng y Oluwakayode Onireti, eds. Radio Access Network Slicing and Virtualization for 5G Vertical Industries. Wiley, 2020. http://dx.doi.org/10.1002/9781119652434.
Texto completoZhuang, Weihua y Qiang Ye. Intelligent Resource Management for Network Slicing in 5G and Beyond. Springer International Publishing AG, 2022.
Buscar texto completoFeng, Gang, Lei Zhang, Oluwakayode Onireti y Arman Farhang. Radio Access Network Slicing and Virtualization for 5G Vertical Industries. Wiley & Sons, Limited, John, 2020.
Buscar texto completoCapítulos de libros sobre el tema "Network slicing in 5G"
Kaloxylos, Alexandros, Christian Mannweiler, Gerd Zimmermann, Marco Di Girolamo, Patrick Marsch, Jakob Belschner, Anna Tzanakaki et al. "Network Slicing". En 5G System Design, 181–205. Chichester, UK: John Wiley & Sons, Ltd, 2018. http://dx.doi.org/10.1002/9781119425144.ch8.
Texto completoCosta-Pérez, Xavier, Andrés Garcia-Saavedra, Fabio Giust, Vincenzo Sciancalepore, Xi Li, Zarrar Yousaf y Marco Liebsch. "Network Slicing for 5G Networks". En 5G Networks: Fundamental Requirements, Enabling Technologies, and Operations Management, 327–70. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781119333142.ch9.
Texto completoKazmi, S. M. Ahsan, Latif U. Khan, Nguyen H. Tran y Choong Seon Hong. "5G Networks". En Network Slicing for 5G and Beyond Networks, 1–12. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16170-5_1.
Texto completoWu, Tin-Yu y Tey Fu Jie. "5G Network Slicing Security". En Advances in Computing, Informatics, Networking and Cybersecurity, 755–80. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-87049-2_28.
Texto completoKazmi, S. M. Ahsan, Latif U. Khan, Nguyen H. Tran y Choong Seon Hong. "Network Slicing: The Concept". En Network Slicing for 5G and Beyond Networks, 13–24. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16170-5_2.
Texto completoKazmi, S. M. Ahsan, Latif U. Khan, Nguyen H. Tran y Choong Seon Hong. "Resource Management for Network Slicing". En Network Slicing for 5G and Beyond Networks, 25–42. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16170-5_3.
Texto completoKazmi, S. M. Ahsan, Latif U. Khan, Nguyen H. Tran y Choong Seon Hong. "Network Slicing: Radio Resource Allocation". En Network Slicing for 5G and Beyond Networks, 43–67. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16170-5_4.
Texto completoBakmaz, Bojan y Miodrag Bakmaz. "5G Network Slicing: Principles, Architectures, and Challenges". En 5G Multimedia Communication, 157–75. First edition. | Boca Raton, FL : CRC Press, 2020.: CRC Press, 2020. http://dx.doi.org/10.1201/9781003096450-8.
Texto completoYe, Qiang y Wen Wu. "Network Slicing for 5G Networks and Beyond". En Wireless Networks, 17–33. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98064-1_2.
Texto completoKazmi, S. M. Ahsan, Latif U. Khan, Nguyen H. Tran y Choong Seon Hong. "Network Slicing: Cache and Backhaul Resource Allocation". En Network Slicing for 5G and Beyond Networks, 91–108. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16170-5_6.
Texto completoActas de conferencias sobre el tema "Network slicing in 5G"
Kaloxylos, Alexandros. "Network slicing for 5G networks". En PCI 2017: 21st PAN-HELLENIC CONFERENCE ON INFORMATICS. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3139367.3139392.
Texto completoJácome, William F. Villota, Oscar M. Caicedo Rendon y Nelson L. S. da Fonseca. "Admission Control and Resource Allocation in 5G Network Slicing". En Anais Estendidos do Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos. Sociedade Brasileira de Computação - SBC, 2021. http://dx.doi.org/10.5753/sbrc_estendido.2021.17158.
Texto completoYoo, Taewhan. "Network slicing architecture for 5G network". En 2016 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2016. http://dx.doi.org/10.1109/ictc.2016.7763354.
Texto completoKourtis, Michail-Alexandros, Themis Anagnostopoulos, Slawomir Kuklilski, Michal Wierzbicki, Andreas Oikonomakis, George Xilouris, Ioannis P. Chochliouros et al. "5G Network Slicing Enabling Edge Services". En 2020 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN). IEEE, 2020. http://dx.doi.org/10.1109/nfv-sdn50289.2020.9289880.
Texto completoAlexander, Henry, Hesham El-Sayed, Manzoor Ahmed Khan y Parag Kulkarni. "Flexibly Controlled 5G Network Slicing". En 2022 5th International Conference on Communications, Signal Processing, and their Applications (ICCSPA). IEEE, 2022. http://dx.doi.org/10.1109/iccspa55860.2022.10019226.
Texto completoSevim, Kubra y Tuna Tugcu. "Handover with Network Slicing in 5G Networks". En 2021 International Conference on Computer, Information and Telecommunication Systems (CITS). IEEE, 2021. http://dx.doi.org/10.1109/cits52676.2021.9618576.
Texto completoAlberti, Antonio Marcos, Karine Costa y Tibério Tavares Tavares Rezende. "Virtualização em Redes Terrestre-Satélite 5G". En I Workshop de Teoria, Tecnologias e Aplicações de Slicing para Infraestruturas Softwarizadas. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/wslice.2019.7723.
Texto completoNoll, Josef, Sudhir Dixit, Danica Radovanovic, Maghsoud Morshedi, Christine Holst y Andrea S. Winkler. "5G network slicing for digital inclusion". En 2018 10th International Conference on Communication Systems & Networks (COMSNETS). IEEE, 2018. http://dx.doi.org/10.1109/comsnets.2018.8328197.
Texto completoChatras, Bruno, U. Steve Tsang Kwong y Nicolas Bihannic. "NFV enabling network slicing for 5G". En 2017 20th Conference on Innovations in Clouds, Internet and Networks (ICIN). IEEE, 2017. http://dx.doi.org/10.1109/icin.2017.7899415.
Texto completoWen, Ruihan, Gang Feng, Jianhong Zhou y Shuang Qin. "Mobility Management for Network Slicing Based 5G Networks". En 2018 IEEE 18th International Conference on Communication Technology (ICCT). IEEE, 2018. http://dx.doi.org/10.1109/icct.2018.8600026.
Texto completoInformes sobre el tema "Network slicing in 5G"
Goreczky, Péter. 5G Network Rollout: a Contest of Countries or Companies? Külügyi és Külgazdasági Intézet, 2021. http://dx.doi.org/10.47683/kkielemzesek.e-2021.14.
Texto completoHousley, R., S. Turner, J. Preuß Mattsson y D. Migault. X.509 Certificate Extension for 5G Network Function Types. RFC Editor, enero de 2023. http://dx.doi.org/10.17487/rfc9310.
Texto completoReddy.K, T., J. Ekman y D. Migault. X.509 Certificate Extended Key Usage (EKU) for 5G Network Functions. RFC Editor, marzo de 2024. http://dx.doi.org/10.17487/rfc9509.
Texto completoWendt-Lucas, Nicola y Ana de Jesus. The Role of 5G in the Transition to a Digital and Green Economy in the Nordic and Baltic Countries: Analytic Report. Nordregio, junio de 2023. http://dx.doi.org/10.6027/r2023:7.1403-2503.
Texto completoAl-Qadi, Imad, Yanfeng Ouyang, Eleftheria Kontou, Angeli Jayme, Noah Isserman, Lewis Lehe, Ghassan Chehab et al. Planning for Emerging Mobility: Testing and Deployment in Illinois. Illinois Center for Transportation, noviembre de 2023. http://dx.doi.org/10.36501/0197-9191/23-025.
Texto completoSzabó, Bianka Emese. China’s Increasing Presence in the ICT Sector in Serbia. Külügyi és Külgazdasági Intézet, 2021. http://dx.doi.org/10.47683/kkielemzesek.ke-2021.19.
Texto completoGarcía Zaballos, Antonio, Maribel Dalio, Jesús Garran, Enrique Iglesias Rodriguez, Pau Puig Gabarró y Ricardo Martínez Garza Fernández. Estructuración de un centro de operación de redes (NOC). Banco Interamericano de Desarrollo, octubre de 2022. http://dx.doi.org/10.18235/0004520.
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