Artículos de revistas: "Network slicing in 5G"

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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.

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Network slicing empowers 5G with enhanced network performance and efficiency, cost saving, and better QoS and customer satisfaction, and expands the commercial application scenarios of 5G networks. However, the introduction of new techniques usually raises new security threats. Most of the existing works on 5G security only focus on 5G itself and do not analyze 5G network slicing security in detail. We consider network slices as a virtual logical network that can unite the subnetwork parts of 5G. If a 5G network slice has security problems or has been attacked, the entire 5G network will have security risks. In this paper, after synthesizing the existing literature, we analyze the security threats step by step through the lifecycle of 5G network slices, analyzing and summarizing more than 70 security threats in three major categories. Based on the security issues investigated, from a viewpoint of building a secure 5G network slicing system, we compiled 24 security requirements and proposed the corresponding recommendations for different scenarios of 5G network slicing. Finally, we collated the future research trends of 5G network slicing security.

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Makhija, 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.

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5G communication systems are being rolled out with multiple technological solutions and applications being fielded on existing as well as enhanced infrastructure. The utilization of 5G systems and infrastructure by verticals over different platforms as well as industries is achieved with slicing. Slicing in 5G provides guaranteed resources for end users of vertical industries and applications over varied platforms, architecture, and infrastructure. Standards for network slicing in 5G have been formulated by 3GPP and further specifications are being released. Implementation of slicing at various layers are being researched. This Paper reviews the advancements in development of specifications for Layer 2 implementation of slicing and communication systems using virtual Private Network and Virtual Transport Network and its architecture. The enhancements to communication systems using existing Multi-Protocol Label Switching (MPLS) and its exploitation based on slicing technology has been reviewed. The research challenges and way ahead on same have been discussed including end resource allocation.

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Munir, 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.

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Network slicing makes it possible for future applications with a variety of adaptability requirements and performance requirements by spliting the physical network into several logical networks. Radio access network (RAN) slicing’s main goal is to assign physical resource blocks (RBs) to mMTC, eMBB, and uRLLC services while ensuring the Quality of service (QoS). Consequently, it is challenging to determine the optimal strategies for 5G radio access network (5G-RAN) slicing because of dynamically changes in slice needs and environmental data, and conventional approaches have difficulty addressing resource allocation issues. In this paper, we present an energy-efficient deep deterministic policy gradient resource allocation (EE-DDPG-RA) method for RAN slicing in 5G networks to choose the resource allocation policy that increases long-term throughput while satisfying the requirements of B5G systems for quality of service. This method’s main goal is to remove unnecessary actions in order to lower the amount of available action space. The numerical outcomes demonstrate that the proposed approach outperforms boundaries by enhancing deep-rooted throughput and effectively managing resources.

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Jia, 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.

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Network slicing has been considered a promising technology in next generation mobile networks (5G), which can create virtual networks and provide customized service on demand. Most existing works on network slicing mainly focus on virtualization technology, and have not considered in-network caching well. However, in-network caching, as the one of the key technologies for information-centric networking (ICN), has been considered as a significant approach in 5G network to cope with the traffic explosion and network challenges. In this article, the authors jointly consider in-network caching combining with network slicing. They propose an efficient caching resource sharing scheme for network slicing in 5G core network, aiming at solving the problem of how to efficiently share the limited physical caching resource of Infrastructure Provider (InP) among multiple network slices. In addition, from the perspective of network slicing, the authors formulate caching resource sharing problem as a non-cooperative game, and propose an iteration algorithm based on caching resource updating to obtain the Nash Equilibrium solution. Simulation results show that the proposed algorithm has good convergence performance, and illustrate the effectiveness of the proposed scheme.

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Wong, 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.

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This article reveals an adequate comprehension of basic defense, security challenges, and attack vectors in deploying multi-network slicing. Network slicing is a revolutionary concept of providing mobile network on-demand and expanding mobile networking business and services to a new era. The new business paradigm and service opportunities are encouraging vertical industries to join and develop their own mobile network capabilities for enhanced performances that are coherent with their applications. However, a number of security concerns are also raised in this new era. In this article, we focus on the deployment of multi-network slicing with multi-tenancy. We identify the security concerns and discuss the defense approaches such as network slice isolation and insulation in a multi-layer network slicing security model. Furthermore, we identify the importance to appropriately select the network slice isolation points and propose a generic framework to optimize the isolation policy regarding the implementation cost while guaranteeing the security and performance requirements.

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Dayot, 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.

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5G networks have been experiencing challenges in handling the heterogeneity and influx of user requests brought upon by the constant emergence of various services. As such, network slicing is considered one of the critical technologies for improving the performance of 5G networks. This technology has shown great potential for enhancing network scalability and dynamic service provisioning through the effective allocation of network resources. This paper presents a Deep Reinforcement Learning-based network slicing scheme to improve resource allocation in 5G networks. First, a Contextual Bandit model for the network slicing process is created, and then a Deep Reinforcement Learning-based network slicing agent (NSA) is developed. The agent’s goal is to maximize every action’s reward by considering the current network state and resource utilization. Additionally, we utilize network theory concepts and methods for node selection, ranking, and mapping. Extensive simulation has been performed to show that the proposed scheme can achieve higher action rewards, resource efficiency, and network throughput compared to other algorithms.

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MAKSYMYUK, 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.

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The paper proposes a new blockchain-based network architecture for 5G network functions virtualization. By using a combination of AI and blockchain technologies, proposed system provides flexible network deployment, interoperability between different mobile network operators and effective management of radio resources. Experimental testbed of the proposed system has been implemented by using cloud and edge computing infrastructure and software defined radio peripheral NI USRP 2900. Simulation results of the network slicing and radio resource management shows that proposed system is able to double the capacity of the physical network infrastructure, while ensuring the target quality of service for all users.

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Kannan, 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.

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The introduction of the fifth-generation (5G) of network technology has radically transformed the telecommunications landscape by providing high-speed, low-latency communication suitable for a range of innovative applications. However, this transformation also introduces novel network complexity and resource management challenges. An emerging solution to these formidable challenges is 'Network Slicing,' a powerful technology that plays a crux role in the efficient management of 5G network systems. Network slicing, enabled by key technologies such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV), allows the creation of multiple virtual and independent networks operating on a shared physical infrastructure. This ability contributes to a more flexible, scalable, and efficient network system, making it aptly suited for diverse 5G applications. In this paper, we conduct an in-depth examination of network slicing in 5G systems, its implementation strategies, associated challenges, and potential solutions. Two real-world case studies underline its practical applications, while a discussion on the future outlook anticipates advances in AI and ML to refine network slicing management. The paper posits that while network slicing brings its own set of complexities, its continuous evolution and relentless innovations gear towards overcoming such challenges, paving the way to a future of 5G networking marked by versatility, reliability, and efficiency of unprecedented levels.

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Dangi, 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.

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Fifth-generation networks efficiently support and fulfill the demands of mobile broadband and communication services. There has been a continuing advancement from 4G to 5G networks, with 5G mainly providing the three services of enhanced mobile broadband (eMBB), massive machine type communication (eMTC), and ultra-reliable low-latency services (URLLC). Since it is difficult to provide all of these services on a physical network, the 5G network is partitioned into multiple virtual networks called “slices”. These slices customize these unique services and enable the network to be reliable and fulfill the needs of its users. This phenomenon is called network slicing. Security is a critical concern in network slicing as adversaries have evolved to become more competent and often employ new attack strategies. This study focused on the security issues that arise during the network slice lifecycle. Machine learning and deep learning algorithm solutions were applied in the planning and design, construction and deployment, monitoring, fault detection, and security phases of the slices. This paper outlines the 5G network slicing concept, its layers and architectural framework, and the prevention of attacks, threats, and issues that represent how network slicing influences the 5G network. This paper also provides a comparison of existing surveys and maps out taxonomies to illustrate various machine learning solutions for different application parameters and network functions, along with significant contributions to the field.

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Sohaib, 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.

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As the idea of a new wireless communication standard (5G) started to circulate around the world, there was much speculation regarding its performance, making it necessary to carry out further research by keeping in view the challenges presented by it. 5G is considered a multi-system support network due to its ability to provide benefits to vertical industries. Due to the wide range of devices and applications, it is essential to provide support for massively interconnected devices. Network slicing has emerged as the key technology to meet the requirements of the communications network. In this paper, we present a review of the latest achievements of 5G network slicing by comparing the architecture of The Next Generation Mobile Network Alliance’s (NGMN’s) and 5G-PPP, using the enabling technologies software-defined networking (SDN) and network function virtualization (NFV). We then review and discuss machine learning (ML) techniques and their integration with network slicing for beyond 5G networks and elaborate on how ML techniques can be useful for mobility prediction and resource management. Lastly, we propose the use case of network slicing based on ML techniques in a smart seaport environment, which will help to manage the resources more efficiently.

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Dongwu, Zhangtao, Chenxiaojin, Zhuhailong y Pengdili. "Research on the Application of 5G Network Slicing in Smart Grid". Journal of Physics: Conference Series 2078, n.º 1 (1 de noviembre de 2021): 012077. http://dx.doi.org/10.1088/1742-6596/2078/1/012077.

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Abstract With the continuous construction and development of domestic power grids, the state has put forward many effective strategies to achieve the effectiveness and durability of energy supply, in order to ensure the stable operation of the power grid and the construction of smart grids. One of the most important components of the smart grid is various communication technologies. 5G network slicing is a typical application of the smart grid, because the wide-area distributed grid has greater requirements for low latency, high reliability and security. And 5G network slicing has the ability to meet its requirements. This paper analyzes the principle of 5G network slicing, analyzes the end-to-end isolation scheme of network slicing and the current smart grid slicing business model and existing problems, and proposes an effective solution for building a smart 5G slicing network.

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Gabilondo, Álvaro, Zaloa Fernández, Roberto Viola, Ángel Martín, Mikel Zorrilla, Pablo Angueira y Jon Montalbán. "Traffic Classification for Network Slicing in Mobile Networks". Electronics 11, n.º 7 (30 de marzo de 2022): 1097. http://dx.doi.org/10.3390/electronics11071097.

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Network slicing is a promising technique used in the smart delivery of traffic and can satisfy the requirements of specific applications or systems based on the features of the 5G network. To this end, an appropriate slice needs to be selected for each data flow to efficiently transmit data for different applications and heterogeneous requirements. To apply the slicing paradigm at the radio segment of a cellular network, this paper presents two approaches for dynamically classifying the traffic types of individual flows and transmitting them through a specific slice with an associated 5G quality-of-service identifier (5QI). Finally, using a 5G standalone (SA) experimental network solution, we apply the radio resource sharing configuration to prioritize traffic that is dispatched through the most suitable slice. The results demonstrate that the use of network slicing allows for higher efficiency and reliability for the most critical data in terms of packet loss or jitter.

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Ray, Debmalya. "Network Type Recognition Using Machine Learning Techniques". INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, n.º 03 (11 de marzo de 2024): 1–13. http://dx.doi.org/10.55041/ijsrem29160.

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The telecom industry is going through a massive digital transformation with the adoption of ML, AI, feedback-based automation and advanced analytics to handle the next generation of applications and services. AI concepts are not new; the algorithms used by Machine Learning and Deep Learning are being currently implemented in various industries and technology verticals. With growing data and an immense volume of information over 5G, the ability to predict data proactively, swiftly and with accuracy, is critically important. Data-driven decision-making will be vital in future communication networks due to the traffic explosion and Artificial Intelligence (AI) will accelerate the 5G network performance. Mobile operators are looking for a programmable solution that will allow them to accommodate multiple independent tenants on the same physical infrastructure and 5G networks allow for end-to-end network resource allocation using the concept of Network Slicing (NS). Network Slicing will play a vital role in enabling a multitude of 5G applications, use cases, and services. Network slicing functions will provide end-to-end isolation between slices with an ability to customize each slice based on the service demands (bandwidth, coverage, security, latency, reliability, etc). Index Terms: Supervised Learning, Feature Engineering, Python, Network Slicing, Telecom, Classification Problems, EDA – Exploratory Data Analysis.

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Gao, Zihang. "Research on 5G Network Slicing Strategy for Urban Complex Environment". Wireless Communications and Mobile Computing 2023 (30 de junio de 2023): 1–11. http://dx.doi.org/10.1155/2023/2820966.

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Focusing on the layout of the 5G mobile communication base station in the city center, we design a 5G city network slicing strategy for the three typical application scenarios with enhanced mobile broadband (eMBB), ultrareliable low-latency communications (URLLC), and massive machine type communications (mMTC). The strategy considers multiple important network performance indicators, including user guaranteed bandwidth, maximum bandwidth limit, QoS (quality of service), link delay tolerance, and slicing throughput. The slicing strategy can greatly increase the connections of base station clients and the utilization of network resources, and effectively reduce block radio and handover radio. The simulation experiments adopt the 5G base station dataset of a coastal city layout in Zhejiang province. Our tests show that the 5G network slicing strategy has certain advantages in network transmission performance in urban complex environment. The research can provide an effective reference for 5G infrastructure construction in other cities.

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Sun, Lei, Li Wang, Peng Yang, Yuqing Zhong, Danke Hong, Guoyi Zhang, Hailong Zhu, Peng Qian y Jing Li. "Implementation and Verification of 5G Network Slicing for Smart Grids". Journal of Physics: Conference Series 2095, n.º 1 (1 de noviembre de 2021): 012019. http://dx.doi.org/10.1088/1742-6596/2095/1/012019.

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Abstract In this paper, 5G slicing networks are proposed to be deployed to address the issues associated with current communication networks in power grid systems and to enable smart grid applications. 5G slice architecture and the corresponding schemes including radio resource reservation, QoS scheduling strategy, VLAN, VPN and 5QI are applied for the access network, the transport network and the core network in the system, based on which a real 5G slicing network is implemented for smart grid applications. It is shown by field trial that the performance requirement regarding service isolation, bandwidth, delay and reliability required by various smart grid applications can be satisfied using the proposed schemes in the real system.

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Kourtis, Michail-Alexandros, Thanos Sarlas, Giorgios Xilouris, Michael C. Batistatos, Charilaos C. Zarakovitis, Ioannis P. Chochliouros y Harilaos Koumaras. "Conceptual Evaluation of a 5G Network Slicing Technique for Emergency Communications and Preliminary Estimate of Energy Trade-Off". Energies 14, n.º 21 (20 de octubre de 2021): 6876. http://dx.doi.org/10.3390/en14216876.

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The definition of multiple slicing types in 5G has created a wide field for service innovation in communications. However, the advantages that network slicing has to offer remain to be fully exploited by today’s applications and users. An important area that can potentially benefit from 5G slicing is emergency communications for First Responders. The latter consists of heterogeneous teams, imposing different requirements on the connectivity network. In this paper, the RESPOND-A platform is presented, which provides First Responders with network-enabled tools on top of 5G on-scene planning, with enhanced service slicing capabilities tailored to emergency communications. Furthermore, a mapping of emergency services and communications to specific slice types is proposed to identify the current challenges in the field. Additionally, the proposed tentative mechanism is evaluated in terms of energy efficiency. Finally, the approach is summarized by discussing future steps in the convergence of 5G network slicing in various areas of emergency vertical applications.

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Larsen, Line M. P., Michael S. Berger y Henrik L. Christiansen. "Fronthaul for Cloud-RAN Enabling Network Slicing in 5G Mobile Networks". Wireless Communications and Mobile Computing 2018 (28 de agosto de 2018): 1–8. http://dx.doi.org/10.1155/2018/4860212.

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This work considers how network slicing can use the network architecture Cloud-Radio Access Network (C-RAN) as an enabler for the required prerequisite network virtualization. Specifically this work looks at a segment of the C-RAN architecture called the fronthaul network. The fronthaul network required for network slicing needs to be able to dynamically assign capacity where it is needed. Deploying a fronthaul network faces a trade-off between fronthaul bitrate, flexibility, and complexity of the local equipment close to the user. This work relates the challenges currently faced in C-RAN research to the network requirements in network slicing. It also shows how using a packet-switched fronthaul for network slicing will bring great advantages and enable the use of different functional splits, while the price to pay is a minor decrease in fronthaul length due to latency constraints.

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Hamza, Hawraa S. y Mehdi Ebady Manaa. "A Developed Multi-Level Deep Learning Model for Network Slicing Classification in 5G Network". Journal of Physics: Conference Series 2701, n.º 1 (1 de febrero de 2024): 012028. http://dx.doi.org/10.1088/1742-6596/2701/1/012028.

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Abstract 5G is considered as a key contributor and infrastructure supplier in the communication technology industry, capable of supporting a wide range of services such as virtual reality, driverless automobiles, e-health, and a variety of intelligent applications. Network slicing is designed to support the diversity of services applications with increased performance and flexibility needs by dividing the physical network into many logical networks. Service classification allows 5G service providers to accurately select the network slices for each service. We propose a Network Slicing classifier that uses a Multi-level Deep learning Model. First, we created a dataset of 5G network slicing that contain attributes connected with various network services. Next, we performed a multi-level model that consist of a set of Machine learning and deep learning model (such as deep Neural Network, Random Forest and Decision Tree) as a first level followed by next level that which is represent Attentive Interpretable Tabular Learning model. The outcomes of the experiment showed that the proposed model was able to exceed the normal models with high performance results.

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Singh, Saurabh, C. Rajesh Babu, Kadiyala Ramana, In-Ho Ra y Byungun Yoon. "BENS−B5G: Blockchain-Enabled Network Slicing in 5G and Beyond-5G (B5G) Networks". Sensors 22, n.º 16 (14 de agosto de 2022): 6068. http://dx.doi.org/10.3390/s22166068.

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Fifth-generation (5G) technology is anticipated to allow a slew of novel applications across a variety of industries. The wireless communication of the 5G and Beyond-5G (B5G) networks will accommodate a wide variety of services and user expectations, including intense end-user connectivity, sub-1 ms delay, and a transmission rate of 100 Gbps. Network slicing is envisioned as an appropriate technique that can meet these disparate requirements. The intrinsic qualities of a blockchain, which has lately acquired prominence, mean that it is critical for the 5G network and B5G networks. In particular, the incorporation of blockchain technology into B5G enables the network to effectively monitor and control resource utilization and sharing. Using blockchain technology, a network-slicing architecture referred to as the Blockchain Consensus Framework is introduced that allows resource providers to dynamically contract resources, especially the radio access network (RAN) schedule, to guarantee that their end-to-end services are effortlessly executed. The core of our methodology is comprehensive service procurement, which offers the fine-grained adaptive allocation of resources through a blockchain-based consensus mechanism. Our objective is to have Primary User—Secondary User (PU—SU) interactions with a variety of services, while minimizing the operation and maintenance costs of the 5G service providers. A Blockchain-Enabled Network Slicing Model (BENS), which is a learning-based algorithm, is incorporated to handle the spectrum resource allocation in a sophisticate manner. The performance and inferences of the proposed work are analyzed in detail.

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Guijarro, Luis, Jose Vidal y Vicent Pla. "Competition in Service Provision between Slice Operators in 5G Networks". Electronics 7, n.º 11 (12 de noviembre de 2018): 315. http://dx.doi.org/10.3390/electronics7110315.

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Network slicing is gaining an increasing importance as an effective way to introduce flexibility in the management of resources in 5G networks. We envision a scenario where a set of network operators outsource their respective networks to one Infrastructure Provider (InP), and use network slicing mechanisms to request the resources as needed for service provision. The InP is then responsible for the network operation and maintenance, while the network operators become Virtual Network Operators (VNOs). We model a setting where two VNOs compete for the users in terms of quality of service, by strategically distributing its share of the aggregated cells capacity managed by the InP among its subscribers. The results show that the rate is allocated among the subscribers at each cell in a way that mimics the overall share that each VNO is entitled to, and that this allocation is the Nash equilibrium of the strategic slicing game between the VNOs. We conclude that network sharing and slicing provide an attractive flexibility in the allocation of resources without the need to enforce a policy through the InP.

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Jain, Anshul, Tanya Singh, Satyendra Kumar Sharma y Vikas Prajapati. "Implementing Security in IoT Ecosystem Using 5G Network Slicing and Pattern Matched Intrusion Detection System: A Simulation Study". Interdisciplinary Journal of Information, Knowledge, and Management 16 (2021): 001–38. http://dx.doi.org/10.28945/4675.

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Aim/Purpose: 5G and IoT are two path-breaking technologies, and they are like wall and climbers, where IoT as a climber is growing tremendously, taking the support of 5G as a wall. The main challenge that emerges here is to secure the ecosystem created by the collaboration of 5G and IoT, which consists of a network, users, endpoints, devices, and data. Other than underlying and hereditary security issues, they bring many Zero-day vulnerabilities, which always pose a risk. This paper proposes a security solution using network slicing, where each slice serves customers with different problems. Background: 5G and IoT are a combination of technology that will enhance the user experience and add many security issues to existing ones like DDoS, DoS. This paper aims to solve some of these problems by using network slicing and implementing an Intrusion Detection System to identify and isolate the compromised resources. Methodology: This paper proposes a 5G-IoT architecture using network slicing. Research here is an advancement to our previous implementation, a Python-based software divided into five different modules. This paper’s amplification includes induction of security using pattern matching intrusion detection methods and conducting tests in five different scenarios, with 1000 up to 5000 devices in different security modes. This enhancement in security helps differentiate and isolate attacks on IoT endpoints, base stations, and slices. Contribution: Network slicing is a known security technique; we have used it as a platform and developed a solution to host IoT devices with peculiar requirements and enhance their security by identifying intruders. This paper gives a different solution for implementing security while using slicing technology. Findings: The study entails and simulates how the IoT ecosystem can be variedly deployed on 5G networks using network slicing for different types of IoT devices and users. Simulation done in this research proves that the suggested architecture can be successfully implemented on IoT users with peculiar requirements in a network slicing environment. Recommendations for Practitioners: Practitioners can implement this solution in any live or production IoT environment to enhance security. This solution helps them get a cost-effective method for deploying IoT devices on a 5G network, which would otherwise have been an expensive technology to implement. Recommendation for Researchers: Researchers can enhance the simulations by amplifying the different types of IoT devices on varied hardware. They can even perform the simulation on a real network to unearth the actual impact. Impact on Society: This research provides an affordable and modest solution for securing the IoT ecosystem on a 5G network using network slicing technology, which will eventually benefit society as an end-user. This research can be of great assistance to all those working towards implementing security in IoT ecosystems. Future Research: All the configuration and slicing resources allocation done in this research was performed manually; it can be automated to improve accuracy and results. Our future direction will include machine learning techniques to make this application and intrusion detection more intelligent and advanced. This simulation can be combined and performed with smart network devices to obtain more varied results. A proof-of-concept system can be implemented on a real 5G network to amplify the concept further.

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Esmaeily, Ali y Katina Kralevska. "Orchestrating Isolated Network Slices in 5G Networks". Electronics 13, n.º 8 (18 de abril de 2024): 1548. http://dx.doi.org/10.3390/electronics13081548.

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Sharing resources through network slicing in a physical infrastructure facilitates service delivery to various sectors and industries. Nevertheless, ensuring security of the slices remains a significant hurdle. In this paper, we investigate the utilization of State-of-the-Art (SoA) Virtual Private Network (VPN) solutions in 5G networks to enhance security and performance when isolating slices. We deploy and orchestrate cloud-native network functions to create multiple scenarios that emulate real-life cellular networks. We evaluate the performance of the WireGuard, IPSec, and OpenVPN solutions while ensuring confidentiality and data protection within 5G network slices. The proposed architecture provides secure communication tunnels and performance isolation. Evaluation results demonstrate that WireGuard provides slice isolation in the control and data planes with higher throughput for enhanced Mobile Broadband (eMBB) and lower latency for Ultra-Reliable Low-Latency Communications (URLLC) slices compared to IPSec and OpenVPN. Our developments show the potential of implementing WireGuard isolation, as a promising solution, for providing secure and efficient network slicing, which fulfills the 5G key performance indicator values.

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Tipantuña, Christian y Xavier Hesselbach. "Adaptive Energy Management in 5G Network Slicing: Requirements, Architecture, and Strategies". Energies 13, n.º 15 (2 de agosto de 2020): 3984. http://dx.doi.org/10.3390/en13153984.

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Energy consumption is a critical issue for the communications network operators, impacting deeply the cost of the services, as well as the ecological footprint. Network slicing architecture for 5G mobile communications enables multiple independent virtual networks to be created on top of a common shared physical infrastructure. Each network slice needs different types of resources, including energy, to fulfill the demands requested by each application, operator, or vertical market. The existing literature on network slicing is mainly targeted at the partition of network resources; however, the corresponding management of energy consumption is an unconsidered critical concern. This paper analyzes the requirements for an energy-aware 5G network slicing provisioning according to the 3GPP specifications, proposes an architecture, and studies the strategies to provide efficient energy consumption in terms of renewable and non-renewable sources. NFV and SDN technologies are the essential enablers and leverage the Internet of Things (IoT) connectivity provided by 5G networks. This paper also presents the technical 5G technology documentation related to the proposal, the requirements for adaptive energy management, and the Integer Linear Programming (ILP) formulation of the energy management model. To validate the improvements, an exact optimal algorithmic solution is presented and some heuristic strategies.

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He, Qi, Yunxia Ju, Jianguo Wang, Gang Zhao, Haiyong Qin, Kai Zhao, Yilan Zhou, Min Li y Qi Dong. "Network Slicing to Enable Resilience and High Availability in 5G Mobile Telecommunications". MATEC Web of Conferences 246 (2018): 03028. http://dx.doi.org/10.1051/matecconf/201824603028.

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In the upcoming fifth-generation (5G) ecosystem, the delivery of a variety of personalized services is envisioned. With the development of software-defined networks and network function virtualization technologies, networks display increasingly flexible features, such as programmability. Network slicing is a state-of-the-art technology that provides services tailored to the specific demands of users, such as smart grids and e-health applications. In this article, we introduce the network slicing concept and its application and discuss related work. In addition, we propose an architecture for network slicing by combining software-defined networks and network function virtualization technologies. Finally, we note important challenges and open issues in the development and application of these technologies.

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25

Esmaeily, Ali y Katina Kralevska. "Small-Scale 5G Testbeds for Network Slicing Deployment: A Systematic Review". Wireless Communications and Mobile Computing 2021 (10 de mayo de 2021): 1–26. http://dx.doi.org/10.1155/2021/6655216.

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Developing specialized cloud-based and open-source testbeds is a practical approach to investigate network slicing functionalities in the fifth-generation (5G) mobile networks. This paper provides a comprehensive review of most of the existing cost-efficient and small-scale testbeds that partially or fully deploy network slicing. First, we present relevant software packages for the three main functional blocks of the ETSI NFV MANO framework and for emulating the access and core network domains. Second, we define primary and secondary design criteria for deploying network slicing testbeds. These design criteria are later used for comparison between the testbeds. Third, we present the state-of-the-art testbeds, including their design objectives, key technologies, network slicing deployment, and experiments. Next, we evaluate the testbeds according to the defined design criteria and present an in-depth summary table. This assessment concludes with the superiority of some of them over the rest and the most dominant software packages satisfying the ETSI NFV MANO framework. Finally, challenges, potential solutions, and future works of network slicing testbeds are discussed.

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26

Olimid, Ruxandra F. y Gianfranco Nencioni. "5G Network Slicing: A Security Overview". IEEE Access 8 (2020): 99999–100009. http://dx.doi.org/10.1109/access.2020.2997702.

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27

Basilier, Henrik, Jan Lemark, Angelo Centonza y Thomas Asberg. "Applied network slicing scenarios in 5G". Ericsson Technology Review 2021, n.º 2 (febrero de 2021): 2–11. http://dx.doi.org/10.23919/etr.2021.9904667.

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28

Hu, Yang, Liangliang Gong, Xinyang Li, Hui Li, Ruoxin Zhang y Rentao Gu. "A Carrying Method for 5G Network Slicing in Smart Grid Communication Services Based on Neural Network". Future Internet 15, n.º 7 (20 de julio de 2023): 247. http://dx.doi.org/10.3390/fi15070247.

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When applying 5G network slicing technology, the operator’s network resources in the form of mutually isolated logical network slices provide specific service requirements and quality of service guarantees for smart grid communication services. In the face of the new situation of 5G, which comprises the surge in demand for smart grid communication services and service types, as well as the digital and intelligent development of communication networks, it is even more important to provide a self-intelligent resource allocation and carrying method when slicing resources are allocated. To this end, a carrying method based on a neural network is proposed. The objective is to establish a hierarchical scheduling system for smart grid communication services at the power smart gate-way at the edge, where intelligent classification matching of smart grid communication services to (i) adapt to the characteristics of 5G network slicing and (ii) dynamic prediction of traffic in the slicing network are both realized. This hierarchical scheduling system extracts the data features of the services and encodes the data through a one-dimensional Convolutional Neural Network (1D CNN) in order to achieve intelligent classification and matching of smart grid communication services. This system also combines with Bidirectional Long Short-Term Memory Neural Network (BILSTM) in order to achieve a dynamic prediction of time-series based traffic in the slicing network. The simulation results validate the feasibility of a service classification model based on a 1D CNN and a traffic prediction model based on BILSTM for smart grid communication services.

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Manbetova, Zhanat, Pavel Dunaev, Manat Imankul y Zhanybek Kaliev. "PROBLEMS OF ORGANIZING THE 5G NETWORK INFRASTRUCTURE". Вестник КазАТК 126, n.º 3 (19 de junio de 2023): 443–50. http://dx.doi.org/10.52167/1609-1817-2023-126-3-443-450.

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Trends in the development of the network infrastructure of future wireless networks have been established. The interrelation between the construction of a network information infrastructure and technologies to reduce the environmental impact in 5G networks is noted. The use of vRAN technology, which allows to reduce total carbon dioxide emissions, is considered. 5G network services are presented, leading to an increase in total energy consumption in these networks. The limitations of the 5G network infrastructure associated with the use of slicing technology are shown.

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Wang, Jiao, Jay Weitzen, Oguz Bayat, Volkan Sevindik y Mingzhe Li. "Performance Model for Video Service in 5G Networks". Future Internet 12, n.º 6 (8 de junio de 2020): 99. http://dx.doi.org/10.3390/fi12060099.

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Network slicing allows operators to sell customized slices to various tenants at different prices. To provide better-performing and cost-efficient services, network slicing is looking to intelligent resource management approaches to be aligned to users’ activities per slice. In this article, we propose a radio access network (RAN) slicing design methodology for quality of service (QoS) provisioning, for differentiated services in a 5G network. A performance model is constructed for each service using machine learning (ML)-based approaches, optimized using interference coordination approaches, and used to facilitate service level agreement (SLA) mapping to the radio resource. The optimal bandwidth allocation is dynamically adjusted based on instantaneous network load conditions. We investigate the application of machine learning in solving the radio resource slicing problem and demonstrate the advantage of machine learning through extensive simulations. A case study is presented to demonstrate the effectiveness of the proposed radio resource slicing approach.

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31

Chinchilla-Romero, Lorena, Jonathan Prados-Garzon, Pablo Ameigeiras, Pablo Muñoz y Juan M. Lopez-Soler. "5G Infrastructure Network Slicing: E2E Mean Delay Model and Effectiveness Assessment to Reduce Downtimes in Industry 4.0". Sensors 22, n.º 1 (29 de diciembre de 2021): 229. http://dx.doi.org/10.3390/s22010229.

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Fifth Generation (5G) is expected to meet stringent performance network requisites of the Industry 4.0. Moreover, its built-in network slicing capabilities allow for the support of the traffic heterogeneity in Industry 4.0 over the same physical network infrastructure. However, 5G network slicing capabilities might not be enough in terms of degree of isolation for many private 5G networks use cases, such as multi-tenancy in Industry 4.0. In this vein, infrastructure network slicing, which refers to the use of dedicated and well isolated resources for each network slice at every network domain, fits the necessities of those use cases. In this article, we evaluate the effectiveness of infrastructure slicing to provide isolation among production lines (PLs) in an industrial private 5G network. To that end, we develop a queuing theory-based model to estimate the end-to-end (E2E) mean packet delay of the infrastructure slices. Then, we use this model to compare the E2E mean delay for two configurations, i.e., dedicated infrastructure slices with segregated resources for each PL against the use of a single shared infrastructure slice to serve the performance-sensitive traffic from PLs. Also we evaluate the use of Time-Sensitive Networking (TSN) against bare Ethernet to provide layer 2 connectivity among the 5G system components. We use a complete and realistic setup based on experimental and simulation data of the scenario considered. Our results support the effectiveness of infrastructure slicing to provide isolation in performance among the different slices. Then, using dedicated slices with segregated resources for each PL might reduce the number of the production downtimes and associated costs as the malfunctioning of a PL will not affect the network performance perceived by the performance-sensitive traffic from other PLs. Last, our results show that, besides the improvement in performance, TSN technology truly provides full isolation in the transport network compared to standard Ethernet thanks to traffic prioritization, traffic regulation, and bandwidth reservation capabilities.

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32

Park, Seok-Woo, Oh-Sung Lee y In-Ho Ra. "5G Network Resource Allocation and Traffic Prediction based on DDPG and Federated Learning". Korean Institute of Smart Media 13, n.º 4 (30 de abril de 2024): 33–47. http://dx.doi.org/10.30693/smj.2024.13.4.33.

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With the advent of 5G, characterized by Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC), efficient network management and service provision are becoming increasingly critical. This paper proposes a novel approach to address key challenges of 5G networks, namely ultra-high speed, ultra-low latency, and ultra-reliability, while dynamically optimizing network slicing and resource allocation using machine learning (ML) and deep learning (DL) techniques. The proposed methodology utilizes prediction models for network traffic and resource allocation, and employs Federated Learning (FL) techniques to simultaneously optimize network bandwidth, latency, and enhance privacy and security. Specifically, this paper extensively covers the implementation methods of various algorithms and models such as Random Forest and LSTM, thereby presenting methodologies for the automation and intelligence of 5G network operations. Finally, the performance enhancement effects achievable by applying ML and DL to 5G networks are validated through performance evaluation and analysis, and solutions for network slicing and resource management optimization are proposed for various industrial applications.

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33

Srinivasan, Thiruvenkadam, Sujitha Venkatapathy, Han-Gue Jo y In-Ho Ra. "VNF-Enabled 5G Network Orchestration Framework for Slice Creation, Isolation and Management". Journal of Sensor and Actuator Networks 12, n.º 5 (13 de septiembre de 2023): 65. http://dx.doi.org/10.3390/jsan12050065.

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Network slicing is widely regarded as the most critical technique for allocating network resources to varied user needs in 5G networks. A Software Defined Networking (SDN) and Network Function Virtualization (NFV) are two extensively used strategies for slicing the physical infrastructure according to use cases. The most efficient use of virtual networks is realized by the application of optimal resource allocation algorithms. Numerous research papers on 5G network resource allocation focus on network slicing or on the best resource allocation for the sliced network. This study uses network slicing and optimal resource allocation to achieve performance optimization using requirement-based network slicing. The proposed approach includes three phases: (1) Slice Creation by Machine Learning methods (SCML), (2) Slice Isolation through Resource Allocation (SIRA) of requests via a multi-criteria decision-making approach, and (3) Slice Management through Resource Transfer (SMART). We receive a set of Network Service Requests (NSRs) from users. After receiving the NSRs, the SCML is used to form slices, and SIRA and SMART are used to allocate resources to these slices. Accurately measuring the acceptance ratio and resource efficiency helps to enhance overall performance. The simulation results show that the SMART scheme can dynamically change the resource allocation according to the test conditions. For a range of network situations and Network Service Requests (NSRs), the performance benefit is studied. The findings of the simulation are compared to those of the literature in order to illustrate the usefulness of the proposed work.

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34

Moreno-Cardenas, Edison y Luis Guijarro. "Market and Sharing Alternatives for the Provision of Massive Machine-Type and Ultra-Reliable Low-Latency Communications Services over a 5G Network". Electronics 12, n.º 24 (13 de diciembre de 2023): 4994. http://dx.doi.org/10.3390/electronics12244994.

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The objective of this paper is to analyze economic alternatives for the provision of ultra-reliable low-latency communication (URLLC) and massive machine-type communication (mMTC) services over a fifth-generation (5G) network. Two business models, a monopoly and a duopoly, are studied and two 5G network scenarios are analyzed: a 5G network where the network resources are shared between the two services without service priority, and a 5G network with network slicing that allows for URLLC traffic to have a higher priority. Microeconomics is used to model the behavior of users and operators, and game theory is used to model the strategic interaction between users and operators. The results show that a monopoly over a 5G network with network slicing is the most efficient way to provide both URLLC and mMTC services.

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35

Hao, Yixue, Daxin Tian, Giancarlo Fortino, Jing Zhang y Iztok Humar. "Network Slicing Technology in a 5G Wearable Network". IEEE Communications Standards Magazine 2, n.º 1 (marzo de 2018): 66–71. http://dx.doi.org/10.1109/mcomstd.2018.1700083.

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36

Al-Aameri, Ali Jasim Ramadhan. "Secure Slicing and Allocation of Resources of 5G Networks In Software-Defined Networking / Network Functions Virtualization". IIUM Engineering Journal 23, n.º 2 (4 de julio de 2022): 85–103. http://dx.doi.org/10.31436/iiumej.v23i2.1763.

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In 5G communications, higher data rates and lower latency are needed due to the high traffic rate. Though resource wastage is avoided by secure slicing, sliced networks are exploited by DDoS attackers. Thus, in the present paper, traffic-aware setting up is PRESENTED for resource allocation and secure slicing over the virtualization of 5G networks enabled by software-defined network/network functions. In the proposed method (called T-S3RA), to authenticate user devices, Boolean logic is used with key derivation based on passwords. Moreover, the traffic arrangement is based on the 5G access points. To implement secure resource allocation and network slicing, deep learning models are used. Renyi entropy computation is employed to predict the DDoS attackers. Through the experimental results, the effectiveness of the presented approach is proved. ABSTRAK: Melalui komunikasi 5G, kadar data yang tinggi dan latensi yang rendah amat diperlukan kerana kadar trafik yang tinggi. Walaupun pembaziran sumber dapat dielakkan melalui pemotongan selamat, rangkaian yang dipotong sering dieksploitasi oleh penyerang DDoS. Oleh itu, kajian ini menyediakan persekitaran sedar-trafik bagi peruntukan sumber dan pemotongan selamat ke atas rangkaian 5G secara maya melalui fungsi rangkaian takrif-perisian. Melaui pendekatan yang dicadangkan (iaitu T-S3RA), peranti pengguna disahkan terlebih dahulu menggunakan logik Boolean dengan perolehan kunci berdasarkan kata laluan. Di samping itu, susunan trafik adalah berdasarkan titik akses 5G. Bagi melaksanakan peruntukan sumber yang selamat dan pemotongan rangkaian, model pembelajaran mendalam telah digunakan. Pengiraan Entropi Renyi dibuat bagi meramal penyerang DDoS. Dapatan eksperimen mengesahkan keberkesanan pendekatan yang dicadangkan.

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37

Escolar, Antonio Matencio, Jose M. Alcaraz-Calero, Pablo Salva-Garcia, Jorge Bernal Bernabe y Qi Wang. "Adaptive Network Slicing in Multi-Tenant 5G IoT Networks". IEEE Access 9 (2021): 14048–69. http://dx.doi.org/10.1109/access.2021.3051940.

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38

Nakao, Akihiro, Ping Du, Yoshiaki Kiriha, Fabrizio Granelli, Anteneh Atumo Gebremariam, Tarik Taleb y Miloud Bagaa. "End-to-end Network Slicing for 5G Mobile Networks". Journal of Information Processing 25 (2017): 153–63. http://dx.doi.org/10.2197/ipsjjip.25.153.

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39

Campolo, Claudia, Ramon Fontes, Antonella Molinaro, Christian Esteve Rothenberg y Antonio Iera. "Slicing on the Road: Enabling the Automotive Vertical through 5G Network Softwarization". Sensors 18, n.º 12 (14 de diciembre de 2018): 4435. http://dx.doi.org/10.3390/s18124435.

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The demanding requirements of Vehicle-to-Everything (V2X) applications, such as ultra-low latency, high-bandwidth, highly-reliable communication, intensive computation and near-real time data processing, raise outstanding challenges and opportunities for fifth generation (5G) systems. By allowing an operator to flexibly provide dedicated logical networks with (virtualized) functionalities over a common physical infrastructure, network slicing candidates itself as a prominent solution to support V2X over upcoming programmable and softwarized 5G systems in a business-agile manner. In this paper, a network slicing framework is proposed along with relevant building blocks and mechanisms to support V2X applications by flexibly orchestrating multi-access and edge-dominated 5G network infrastructures, especially with reference to roaming scenarios. Proof of concept experiments using the Mininet emulator showcase the viability and potential benefits of the proposed framework for cooperative driving use cases.

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40

Kochetkova, Irina, Kseniia Leonteva, Ibram Ghebrial, Anastasiya Vlaskina, Sofia Burtseva, Anna Kushchazli y Konstantin Samouylov. "Controllable Queuing System with Elastic Traffic and Signals for Resource Capacity Planning in 5G Network Slicing". Future Internet 16, n.º 1 (31 de diciembre de 2023): 18. http://dx.doi.org/10.3390/fi16010018.

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Fifth-generation (5G) networks provide network slicing capabilities, enabling the deployment of multiple logically isolated network slices on a single infrastructure platform to meet specific requirements of users. This paper focuses on modeling and analyzing resource capacity planning and reallocation for network slicing, specifically between two providers transmitting elastic traffic, such during as web browsing. A controller determines the need for resource reallocation and plans new resource capacity accordingly. A Markov decision process is employed in a controllable queuing system to find the optimal resource capacity for each provider. The reward function incorporates three network slicing principles: maximum matching for equal resource partitioning, maximum share of signals resulting in resource reallocation, and maximum resource utilization. To efficiently compute the optimal resource capacity planning policy, we developed an iterative algorithm that begins with maximum resource utilization as the starting point. Through numerical demonstrations, we show the optimal policy and metrics of resource reallocation for two services: web browsing and bulk data transfer. The results highlight fast convergence within three iterations and the effectiveness of the balanced three-principle approach in resource capacity planning for 5G network slicing.

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41

Gomes, Rayner, Dario Vieira y Miguel Franklin de Castro. "Application of Meta-Heuristics in 5G Network Slicing: A Systematic Review of the Literature". Sensors 22, n.º 18 (6 de septiembre de 2022): 6724. http://dx.doi.org/10.3390/s22186724.

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Network slicing is a vital component of the 5G system to support diverse network scenarios, creating virtual networks (slices) by mapping virtual network requests to real networks. The mapping is an arduous computing process, mathematically studied and known as the Virtual Network Embedding (VNE) problem, and its complexity is NP-Hard. The mapping process is oriented to respect the QoS demands from the virtual network requests and the available resources in the physical-substrate infrastructure. Meta-heuristic approaches are a suitable way to solve the VNE problems because of their capacity to escape from the local optimum and adapt the solution search to complex networks; these abilities are essential in 5G networks scenarios. This article presents a systematic review of meta-heuristics organized by application, development and problem-solving approaches to VNE. It also provides the standard parameters to model the infrastructure and virtual network requests to simulate network slicing as a service. Finally, our work proposes some future research based on the discovered gaps.

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42

Dan, Wang, Zhao Xunwei, Bai Jie, Wu Qing y Wang Wenhua. "An study on the application of blockchain based 5G Technology in the Power IoT". E3S Web of Conferences 252 (2021): 01032. http://dx.doi.org/10.1051/e3sconf/202125201032.

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Based on some key characteristics of 5G and blockchain, we analyze the technical feasibility and necessity of combining 5G and blockchain in IoT construction. We prove that the combination of 5G and blockchain can effectively improve network and data security of 5G by discussing the practical problems that can be solved by this method(including distributed deployment of network platforms, slicing management, network security authentication, spectrum resource management, data sharing security), while moderately reducing network complexity. Finally, we discuss the application of 5G and blockchain combined technical architecture in the construction of the Internet of Things (IoT), focusing on the requirements of power transmission, substation, distribution and consumption. We analyze the 5G network slicing management based on blockchain technology, which can realize the dynamic selection of the best resources among multiple resources to create end-to-end network slices that meet business needs and security isolation requirements, and enhance the security of the network and the data in multiple scenarios and applications, it will provide a strong network infrastructure support for the Energy IoT service system.

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43

Onopa, Serhii y Zbigniew Kotulski. "State-of-the-Art and New Challenges in 5G Networks with Blockchain Technology". Electronics 13, n.º 5 (3 de marzo de 2024): 974. http://dx.doi.org/10.3390/electronics13050974.

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As mobile communications transform, 5G technology can potentially change many industries and businesses. The change will have a great influence across many fields, such as the automotive, healthcare, and manufacturing sectors. This paper aims to review the existing applications of blockchain technology in providing 5G network security and identify new possibilities for such security solutions. We consider different aspects of blockchain in 5G, particularly data transmission, access control, and applications including vertical industry-oriented applications and specific solutions supporting such sectors of economic activity. The paper briefly describes modern technologies in 5G networks and introduces blockchain’s properties and different aspects of using such technology in practical applications. It also presents access control management with blockchain applied in 5G and related problems, reviews other blockchain-enforced network technologies, and shows how blockchain can help in services dedicated to vertical industries. Finally, it presents our vision of new blockchain applications in modern 5G networks and beyond. The new-generation networks use two fundamental technologies, slicing and virtualization, and attackers attempt to execute new types of attacks on them. In the paper, we discuss one of the possible scenarios exhibiting the shortcomings of the slicing technology architecture. We propose using blockchain technology to create new slices and to connect new or existing subscribers to slices in the 5G core network. Blockchain technology should solve these architectural shortcomings.

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44

AFOLABI, Ibrahim, Adlen KSENTINI, Miloud BAGAA, Tarik TALEB, Marius CORICI y Akihiro NAKAO. "Towards 5G Network Slicing over Multiple-Domains". IEICE Transactions on Communications E100.B, n.º 11 (2017): 1992–2006. http://dx.doi.org/10.1587/transcom.2016nni0002.

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45

Zhang, Shunliang. "An Overview of Network Slicing for 5G". IEEE Wireless Communications 26, n.º 3 (junio de 2019): 111–17. http://dx.doi.org/10.1109/mwc.2019.1800234.

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46

Foukas, Xenofon, Georgios Patounas, Ahmed Elmokashfi y Mahesh K. Marina. "Network Slicing in 5G: Survey and Challenges". IEEE Communications Magazine 55, n.º 5 (mayo de 2017): 94–100. http://dx.doi.org/10.1109/mcom.2017.1600951.

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47

Li, Xin, Mohammed Samaka, H. Anthony Chan, Deval Bhamare, Lav Gupta, Chengcheng Guo y Raj Jain. "Network Slicing for 5G: Challenges and Opportunities". IEEE Internet Computing 21, n.º 5 (2017): 20–27. http://dx.doi.org/10.1109/mic.2017.3481355.

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48

Yao, Yizhi y Xiaowen Sun. "Performance Assurance for 5G NetworksIncluding Network Slicing". Journal of ICT Standardization 7, n.º 2 (2019): 93–108. http://dx.doi.org/10.13052/jicts2245-800x.722.

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49

Yao, Yizhi y Xiaowen Sun. "Performance Assurance for 5G NetworksIncluding Network Slicing". Journal of ICT Standardization 7, n.º 2 (2019): 93–108. http://dx.doi.org/10.13052/jicts2245-800x.7232.

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Goldstein, B., V. Elagin, K. Kobzev y A. Grebenshchikova. "An Introduction to 5G Network Slicing Technology". Telecom IT 7, n.º 4 (31 de diciembre de 2019): 21–29. http://dx.doi.org/10.31854/2307-1303-2019-7-4-21-29.

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Communications Service Providers are looking to 5G technology as an enabler for new revenues, with network slicing providing a cost-effective means of supporting multiple services on shared infrastructure. Different radio access technologies, network architectures, and core functions can be brought together under software control to deliver appropriate Quality of Service “slices,” enabling new levels of service innovation, such as high bandwidth for video applications, low latency for automation, and mass connectivity for Smart Cities.

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