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In this article, we deal with the enhanced Mobile Broadband (eMBB) service class, defined within the new 5G communication paradigm, to evaluate the impact of the transition from 4G to 5G access technology on the Radio Access Network and on the Transport Network. Simulation results are obtained with ns3 and performance analyses are focused on 6 GHz...
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... simulation scenario is shown in Figure 4 where the eNodeB (red node) is connected directly to the PGW/ SGW node (green node) via a dedicated point-to-point physical connection (gray lines). To measure the network performance at the connection point between the RAN and the transport network, in this first set of simulations the PGW/SGW node has been directly connected to a second node (yellow node), representing a network server. ...
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Fifth generation networks are the area in which a lot of researchers are spending their time to enhance its performance as per dynamic change in wireless communication. The essential utilization of such a technique (5G) is used to have higher data rates containing minimum latency. The data rate of 5G technology is usually gigabits per second (Gbps)...
Citations
... In [15], researchers discuss promising aspects of 5G networks, the need for a comprehensive simulation environment, and contributions related to evaluating radio access technologies and SDN impact on the transport segment. Moreover, a case study of using ns-3 to realize various architectures for Data Center Networks (DCNs) and study their performance is presented in [16]. ...
... The work in [12] relies on analytical modeling and simulations to evaluate the proposed model's effectiveness causing the lack of real-world testing. The study in, [15] offers adaptable 5G simulation for analyzing varied network configurations and their performance outcomes. While useful, ns3's capacity for simulating real-world behaviors may be limited in certain contexts, particularly regarding research on VNF placement on hardware components. ...
Service Function Chain (SFC) provisioning stands as a pivotal technology in the realm of 5G and future networks. Its essence lies in orchestrating VNFs (Virtual Network Functions) in a specified sequence for different types of SFC requests. Efficient SFC provisioning requires fast, reliable, and automatic VNFs' placements, especially in a network where massive amounts of SFC requests are generated having ultra-reliable and low latency communication (URLLC) requirements. Although much research has been done in this area, including Artificial Intelligence (AI) and Machine Learning (ML)-based solutions, this work presents an advanced Deep Reinforcement Learning (DRL)-based simulation model for SFC provisioning that illustrates a realistic environment. The proposed simulation platform can handle massive heterogeneous SFC requests having different characteristics in terms of VNFs chain, bandwidth, and latency constraints. Also, the model is flexible to apply to networks having different configurations in terms of the number of data centers (DCs), logical connections among DCs, and service demands. The simulation model components and the workflow of processing VNFs in the SFC requests are described in detail. Numerical results demonstrate that using this simulation setup and proposed algorithm, a realistic SFC provisioning can be achieved with an optimal SFC acceptance ratio while minimizing the E2E latency and resource consumption.
... Despite that, the work is limited to the number of users, ignoring other important 5G key factors. The authors in [19] consider 1, 10, and 100 users in 5G networks to measure throughput, delay, and jitter in 5G networks with no regard to other 5G performance affecting factors. The increasing number of users is also taken into account in [20] for the Internet of Vehicles (10,20,30,40,50, and 60 active vehicles). ...
The feature-rich nature of 5G introduces complexities that make its performance highly conditional and dependent on a broad range of key factors, each with unique values and characteristics that further complicate 5G deployments. To address the complexities, this work develops a new modular model based on machine learning on both architecture and service factors (5GPA) that actively contribute to variations in 5G network performance. The objectives are to address the complications during the design and planning phases according to the requirements before 5G deployment, simplify the whole feature-selection process for different deployments, and optimize 5G network performance. The model is implemented and the results are utilized to determine the correlation between the 5GPA factors and the overall performance. Additionally, a simulated 5G dataset is generated and utilized to make predictions on 5G performance based on unseen factors and values of interest. The reliability of the model is validated by comparing the predicted and actual results in the context of quality of service requirements. The results represent a high level of accuracy, with an average of 95%, and low error rates in terms of mean absolute error, mean squared error, and root mean squared error, averaging 7.60e−03, 1.18e−04, and 8.77e−03, respectively.
... This is measured by the total round trip time of a data packet between the robot surgeon to the remote patient console and back. 5. Below are the tools and software we used for testing the different scenarios based on the literature survey of existing experiments that were carried out. o Network simulation software: NS-3 was used to simulate the network environment and test the performance of the proposed solution under different network loads and conditions [8]. o Attack simulation tools: Metasploit was used to simulate network attacks. ...
The adoption of robotic surgical procedures over wireless 5G networks has increased rapidly in recent years, providing improved precision and patient outcomes. However, the security and reliability of the end-to-end information between the surgeon's control console and the robotic system are critical concerns. This paper proposes a solution to enhance the security and reliability of the authentication process in robot-assisted surgery by enhancing existing authentication mechanisms. The proposed solution builds upon the existing Transport Layer Security (TLS) protocol, and introduces additional security measures, including biometric authentication and multi-factor authentication while minimizing latency and delay in transmission. The effectiveness of the proposed solution is evaluated through simulation and testing, demonstrating its ability to provide enhanced security for robot-assisted surgery. The proposed solution has the potential to provide an additional layer of security while staying in realistic bounds of latency and delay in data transmission.
... To reduce the congestion in the LTE network, the transmitting flexibility and its cost have to be minimized; because 5G demands new ideas and designs for the portable device [2]. Currently, achieving complete SDN organization in a short period is impossible for network administrators, as the task necessitates various changes to existing organizing technology and the replacement of overly expensive items [3,4]. SDN does have its own set of challenges and roadblocks, including implementation issues to questions regarding logical centralization guarantees [5]. ...
... In this model, the image observation symbol O represents a three-dimensional predictions, specifically, the objects speed, direction and location concerning the current access point, which are described in Eqs. (4)(5)(6)(7), ...
In recent years, the 5G network faces more traffic congestion due to the increasing number of mobile operators. In the networking field, learning methods are widely used to reduce the cost and increase flexibility and scalability. Network Function Virtualization is used to set the hardware functions as well as Software-Defined Networking (SDN) helps to concentrate the programming setup. SDN is a key method designed at sustaining high data traffic in next-generation 5G networks. Conversely, the compact deployment of small cells introduces numerous challenges such as frequent handovers, inconsistencies, interfaces, and so on. The software-defined 5G network is one important technique to solve these problems. Moreover, due to the separation of control and data signaling in 5G technology, the operation of handover should be performed. Therefore, Multiplicative Long Short-Term Memory (mLSTM)-based resource estimation strategy is proposed in this study to solve the handover problem. Finally, analyze the observed delays using the densification ratio metric to evaluate the standard and suggested handover procedures for proposed mLSTM which depends on user count. While related to the traditional SDN technique, the proposed mLSTM reduces the handover delay by 4.28 ms.
... Step 1: An initial NS3 is created with seven (n) controllers, twenty-eight (n) switches, and forty-five (n) users [32]. ...
The multi-controller placement problem (MCPP) represents one of the most challenging issues in software-defined networks (SDNs). High-efficiency and scalable optimized solutions can be achieved for a given position in such networks, thereby enhancing various aspects of programmability, configuration, and construction. In this paper, we propose a model called simulated annealing for multi-controllers in SDN (SA-MCSDN) to solve the problem of placing multiple controllers in appropriate locations by considering estimated distances and distribution times among the controllers, as well as between controllers and switches (C2S). We simulated the proposed mathematical model using Network Simulator NS3 in the Linux Ubuntu environment to extract the performance results. We then compared the results of this single-solution algorithm with those obtained by our previously proposed multi-solution harmony search particle swarm optimization (HS-PSO) algorithm. The results reveal interesting aspects of each type of solution. We found that the proposed model works better than previously proposed models, according to some of the metrics upon which the network relies to achieve optimal performance. The metrics considered in this work are propagation delay, round-trip time (RTT), matrix of time session (TS), average delay, reliability, throughput, cost, and fitness value. The simulation results presented herein reveal that the proposed model achieves high reliability and satisfactory throughput with a short access time standard, addressing the issues of scalability and flexibility and achieving high performance to support network efficiency.
... Modeling of the SDN network was performed in the Network Simulator version 3 (NS3) [(ns-3.35, 2021); (Lavacca et al., 2020)]. To assess the efficiency of the clustering subsystem, five unauthorized nodes were created that generated atypical packets in the general stream once per second on average. ...
The article deals with the creation of an intelligent architecture of the Internet of Things transport environment based on software-defined network (SDN) and blockchain for detecting threats and attacks. The transport environment is created for the monitoring system of critical events in the road transport infrastructure. Blockchain technology is used to authenticate network nodes, store sensor data in a distributed ledger. The network packet clustering method based on a fuzzy neural network is used to detect packets with possible malicious content. The intelligent SDN architecture is a hierarchy of four layers with six levels and includes: a) edge computing layer (sensor nodes and routers level, SDN switches data level), b) fog computing layer (zone server level, control level in SDN controllers), c) a cloud computing layer with data center servers, d) a layer for presenting monitoring results on user devices and applications. Detection of threats and attacks is implemented by validating network nodes and analyzing header fields of IP packets and TCP segments. The intrusion detection system includes a parser and analyzer of data packets, a module for filtering traffic by type, port numbers and other characteristics of packets, a module for synthesizing digital signatures of trusted nodes and their validation, a module for analyzing and clustering packets based on fuzzy logic and a neural network, modules for logging procedures. The probability function of packets belonging to clusters is tuned through deep learning of a five-layer neural network. The conclusion about belonging and degree of similarity with malicious packages is formed using the fuzzy logic apparatus. To train the neural network, the previously synthesized rules of the flow tables and the identified signs of atypical data packets are used. The functionality and effectiveness of the SDN architecture with an intrusion detection system is validated by simulating procedures in the NS3 Simulator system, evaluating authenticity, latency, throughput, response time, and accuracy in detecting atypical data packets.
... When different networks types interact with each other, the analysis of the behavior of their models implemented with the simulator is also used. For instance, the project to performance evaluation of 5G access technologies and the SDN transport network [35] analyses traffic carried out during transmission in mobile networks of the 4th and 5th generations to the transport SDN network. The estimation results showed that eMBB traffic transmitted by 5G networks is more suitable for interacting with SDN than 4G networks, and, also, the transition to a new mobile network generation makes absolute sense from the point of this issue view. ...
The determining factor in the accelerated pace of informatization is the increase in the speed and reliability of data transmission networks. In this regard, new and existing standards are developed and modernized. A lot of organizations are constantly working on the development and implementation of new generation communication networks. This article provides an overview of available software solutions that allow us to investigate and evaluate the behavior of data networks. In particular, tools suitable for mobile communication systems were determined, having sufficient built-in functionality and allowing us to add our own implementations. NS3 has been chosen as a suitable network simulator. Apart from the review, a solution for this tool was developed. It allows estimating the reliability of data transmission from the start movement of a network node at all times during its removal from a base station.
... Furthermore, an endto-end 5G network can adopt specific architectures to obtain data pre-processing, in specific areas as in the edge, according to Edge and Fog models [7][8]. All these considerations make it very difficult to have a single simulation tool to investigate such a broad environment and our experience [9] leads us to conclude that currently there are two main simulation platforms that better operate with respect to others: ns3 for the radio access segment and Mininet for the core segment. Mininet showed important features for the SDN environment, but it currently does not support modelling of wireless channel and mobility [10]. ...
... Simulation results were obtained below 6 GHz radio scenarios, where it has been assumed a "non-Standalone 5G configuration", and on SDN-based scenarios for the Transport Network. In this paper we show instead how Mininet allows us to leverage a Fog architecture and how, via ns3, it is possible to extend the radio access segment presented in [9] to include the NLoS environment and the propagation above 6GHz (26 GHz). For brevity's sake this paper focuses on a limited, yet significant, number of cases, showing the potential of a ns3-Mininet platform to study an end-to-end 5G network simulation tool. ...
... Ns-3 has been already adopted for investigating core behaviour and for simulating OpenFlow behaviour as described in [9]. This framework, however, shows some limitations as concerns SDN paradigm, in contrast to Mininet which does not support modelling of wireless channel and mobility, but shows very appealing results for SDN investigations. ...
... The technology of 5G has been set the reliable and trusted network. For the business and IOT application the role of 5G speed is important [24]. The architecture of the 5G is combination of the 3G, GPRS and LTE. ...
In the modern era of technology, the high speed internet is the most important part of human life. The current available network is reckoned to be slow in speed and not be up to snuff for data transmission regarding business applications. The objective of handover mechanism is to reassign the current session handle by internet gadget. The globe needs the next generation high mobility and throughput performance based internet model. This research paper explains the proposed method of design and development for handover based 5G cellular network. In comparison to the traditional method, we propose to control the handovers between base-stations using a concentric method. The channel simulator is applied over the range of the frequencies from 500 MHz to 150 GHz and radio frequency for the 700 MHz bandwidth. The performance of the simulation system is calculated on the basis of handover preparation and completion time regarding base station as well as number of users. From this experiment we achieve the 7.08 ms handover preparation time and 9.98 ms handover completion time. The author recommended the minimum handover completion time, perform the high speed for 5G cellular networks.
