Quality Of Service Parameters Research Articles

Comparative Analysis of Quality of Service (QoS) on WLAN Network Bandwidth Management using HTB Method with PCQ

This study explores bandwidth management on WLAN networks using Hierarchical Token Bucket (HTB) and Per Connection Queue (PCQ) methods to optimize Quality of Service (QoS). With the growing role of IT in both business and public sectors and increasing WLAN access, effective bandwidth management has become crucial to prevent certain users from monopolizing bandwidth for upload or download activities. The research involves data collection through observation and literature review, designing a network topology, implementing bandwidth management using HTB and PCQ, and analyzing performance with QoS parameters: throughput, delay, jitter, and packet loss. The results show that the HTB method achieves an average throughput of 97%, a delay of 98 ms, a jitter of 77 ms, and no packet loss, making it ideal for networks requiring priority-based bandwidth allocation for performance-sensitive applications. In contrast, the PCQ method yields an average throughput of 93.5%, a delay of 217 ms, a jitter of 55 ms, and no packet loss, which is better suited for evenly distributing bandwidth among users. Thus, HTB is recommended for priority-based networks, while PCQ supports fair bandwidth distribution across users.

Review of QoS-aware resource allocation schemes for 5g networks

Resource management in wireless networks refers to the processes and techniques used to allocate, control, and optimize the various resources in a wireless communication system to ensure efficient and reliable operation. These resources typically include spectrum (frequency bands), power, time slots, and network infrastructure (e.g., base stations, access points). Effective resource management is crucial for maximizing network performance, ensuring Quality of Service (QoS), and providing a good user experience, especially in environments with limited resources and high demand. Quality of Service (QoS) refers to the ability of the network to provide different levels of service quality to various types of traffic, applications, and users. QoS in 5G is essential due to the diverse range of services the network is designed to support, each with its own specific requirements for performance metrics such as latency, reliability, bandwidth, and availability. In this paper, we study how the QoS-aware resource allocation procedure is handled in wireless networks. Different resource management techniques were studied and also the paper looked at some of the existing QoS-aware resources allocation schemes by highlighting the operation, strength and weakness and the QoS parameters considered by each of the schemes.

Maximizing energy efficiency in HetNets through centralized and distributed sleep strategies under QoS constraint

This research addresses the critical need to optimize the Energy Efficiency (EE) for Ultra-Dense HetNets amid the ever-increasing demands for high-speed data networks. The rapid increase in high-speed devices highlights the urgent necessity for a transformative change in upcoming 5G cellular networks. According to Ericsson's 2022 report, mobile data traffic volume is expected to double by 2027, with mobile video traffic anticipated to rise by nearly 30% each year. In response to these challenges, researchers have identified essential technologies that facilitate 5G networks, including massive Multiple-input-Multiple-output (m-MIMO) systems and HetNets. Although both promise enhanced coverage and throughput, HetNets emerges as a cost-effective solution, surpassing m-MIMO in implementation cost and coverage. However, achieving maximum EE in HetNets necessitates careful consideration of various constraints, including delay, coverage probability, and Signal-to-Interference-plus-Noise Ratio (SINR) thresholds. This research marks a significant milestone in adopting the Distributed Dynamic Opportunistic Sleep Strategy (D-DOSS) approach. The D-DOSS method organizes small clusters throughout the network and evaluates key Quality of Service (QoS) parameters including Energy Utilization Efficiency (EUE), Coverage Probability, Data Throughput, and Success Probability using Monte Carlo simulations. This research analyzes Distributed Sleep (DS) and Centralized Schemes (CS) concerning given QoS parameters. While DS methodologies often exhibit performance trade-offs compared to CS, they provide significant advantages in terms of ease of implementation and management. CS, though representing the most commonly used method in ultra-dense HetNets involves high computational costs that complicate its management. By integrating the D-DOSS and addressing various constraints, this research not only advances HetNet technologies but also makes a significant contribution to optimizing EE while preserving network performance and QoS. The innovative D-DOSS approach offers a promising solution to the challenges of energy efficiency in wireless communication networks and paves the way for future advancements in HetNet deployments. The results and analysis show that D-DOSS effectively addresses the limitations of DS and outperforms existing CS techniques.

Traffic Engineering with Specified Quality of Service Parameters in Software-defined Networks

A method of traffic engineering (TE) based on the method of multi-path routing is proposed in the study. Today, one of the main challenges in networking is to organize an efficient TE system that will provide such parameters of quality of service (QoS) as the allowable value of packet loss and time for traffic re-routing. Traditional one-way routing facilities do not provide the required quality of service (QoS) parameters for TE. Modern computer networks use static and dynamic routing algorithms, which are characterized by big time complexity and a large amount of service information. This negatively affects the overall state of the network, namely: leads to network congestion, device failure, loss of information during routing and increases the time for traffic re-routing. Research has shown that the most promising way to solve the TE problem in computer networks is a comprehensive approach, which consists of multi-path routing, SDN technology and monitoring of the overall situation of the network. This paper proposes a method of traffic engineering in a software-defined network with specified quality of service parameters, which has reduced the time of traffic re-routing and the percentage of packet loss due to the combination of the centralized TE method and multi-path routing. From a practical point of view, the obtained method, will improve the quality of service in computer networks in comparison with the known method of traffic construction.

Analisis Penggunaan Metode XConnect Main and Backup Link Berbasis VPN MPLS Layer 2 pada Jaringan Metro-Ethernet

The rapid development of information and communication technology requires excellent scalability, which is crucial for network performance availability. MPLS is a technology that can be used for communication in high-speed backbone networks based on virtual private networks (VPN). MPLS provides solutions to various current computer network problems such as speed, scalability, quality of service (QoS), and network traffic management. This research aims to optimize the scalability of MPLS Layer 2 VPN-based network traffic by applying the xconnect main and backup method implemented in metro Ethernet networks. The network simulation implementation was created using the Emulated Virtual Environment – Next Generation (EVE-NG) application to obtain data on convergence time and QoS parameters according to TIPHON standards, as well as the use of MPLS and Route Reflector to enhance MPLS backbone performance. This research shows that both main and backup MPLS L2VPN paths have good index values in packet delivery according to TIPHON standards, with an average rating of 3.0. Thus, this research can help optimize path scalability to improve the quality of MPLS L2VPN network traffic.

Multi-objective QoS optimization in swarm robotics

The “Internet of Robotic Things” (IoRT) is a concept that connects sensors and robotic objects. One of the practical applications of IoRT is swarm robotics, where multiple robots collaborate in a shared workspace to accomplish assigned tasks that may be challenging or impossible for a single robot to conquer. Swarm robots are particularly useful in critical situations, such as post-earthquake scenarios, where they can locate survivors and provide assistance in areas inaccessible to humans. In these life-saving situations, reliable and prompt communication among swarm robots is of utmost importance. To address the need for highly dependable and low-latency communication in swarm robotics, this research introduces a novel hybrid approach called Multi-objective QoS optimization based on Support vector regression and Genetic algorithm (MQSG). The MQSG method consists of two main phases: Parameter Relationship Identification and Parameter Optimization. In the Parameter Relationship Identification phase, the relationship between network inputs (Packet inter-arrival time, Packet size, Transmission power, Distance between sender and receiver) and outputs (quality of service (QoS) parameters) is established using support vector regression. In the parameter optimization phase, a multi-objective function is created based on the obtained relationships from the Parameter Relationship Identification phase. By solving this multi-objective function, optimal values for each QoS parameter are determined, leading to enhanced network performance. Simulation results demonstrate that the MQSG method outperforms other similar algorithms in terms of transmission latency, packet delivery rate, and the number of retransmitted packets.

A QoS Analysis of SHA Algorithms for IoT Systems

Secure Hash Algorithms (SHA) are widely used in the Internet of Things (IoT) systems for message authentication and integrity verification. However, the performance of different SHA algorithms can vary significantly in terms of Quality of Service (QoS) metrics such as area utilization, processing speed, energy efficiency, and security. In this paper, we present a comprehensive analysis of the QoS parameters of various SHA algorithms and discuss the trade-offs between performance and security when selecting SHA algorithms for resource-constrained IoT devices. The study focuses on the hardware implementation of SHA algorithms in Field-Programmable Gate Array (FPGA) devices, which are commonly used in IoT applications. The performances and resource utilization of different SHA algorithms are compared and analyzed. The comparative results show that SHA-2 provide a good balance between performance and security, but SHA-3 provide better security due to its resistance to attacks such as length extension and collision

Distortion‐less video wireless transmission in 5G new radio using delay‐distortion‐rate optimization (DDRO)

SummaryIn this paper, a novel strategy of video communication over a 5G platform of new radio (NR) is developed, and it is named ViNR. With the support of optimization on the ViNR quality of service (QoS) system design, we stretched the outdated R‐D optimization to a novel delay‐distortion‐rate optimization (DDRO) control method. The entire model is partitioned with two types of coding: source coding and channel coding. For source coding, we affianced the inter‐frame prediction method of independent predicted frames (IPPPP) with Lagrange multiplier optimization. Channel coding is intricate with the minimization of delay‐distortion and getting the most out of the rate using resource allocation optimization in terms of sub‐slice allocation. To perform this sub‐slice resource assignment with optimization of DDR, the isolation resource allocation is premeditated in this work to ensure the service level profile of various groups of resource slots or grids dealing with the subject of middling delay and rate. The widespread simulation results divulge that the proposed algorithm NR‐DDRO achieves better QoS parameters of delay, distortion, and rate with the metrics of end‐to‐end distortion, encoding Y‐PSNR, encoding bit rate, encoding time, end‐to‐end PSNR, optimization time, and complete computation time.

Fuzzy logic‐based computation offloading technique in fog computing

AbstractThe fog computing environment expands the capabilities of cloud computing by moving computing, storage, and networking services closer to IoT devices. These resource‐constrained IoT devices often face challenges like high task failure rates and extended execution latency due to data traffic congestion. Distributing IoT services through task offloading across different layers of computing paradigms enhances QoS (Quality of Service) parameters. This endeavor aims to allocate custom workflow‐based real‐time tasks or jobs for processing across various cloud/fog/edge layers, optimizing QoS factors like makespan, energy consumption, and cost. In the fog computing environment, challenges arise due to uncertainties related to job execution locations and the ability to predict future user requirements. Fuzzy logic offers low‐complexity solutions for handling unpredictable and rapidly changing conditions. This paper proposes a hybrid fog‐cloud‐based computing architecture and an intelligent fuzzy logic‐based computation offloading approach. This approach effectively allocates workloads among edge, fog, and cloud layers, resulting in improvements in makespan time (7.51%), energy consumption (4.63%), and cost (13.60%). The proposed method selects suitable processing units or compute nodes for job execution, utilizing heterogeneous resources. Simulation results demonstrate that the proposed methodology outperforms current state‐of‐the‐art algorithms.

IoT-based MANET performance improvement against jamming attackers in different mobile applications

Internet of Things (IoT) is a cutting-edge technology and effective solution that enables real-time communication between physical objects. In order to manage the mobility of nodes in the IoT, mobile ad hoc networks (MANETs) are crucial. It enables IoT-based systems to construct and connect networks autonomously. IoT based MANET is more vulnerable to Jamming attacks (Jammers) due to the decentralized nature of the ad hoc network. Therefore, secure communication is a crucial requirement for nodes. In this paper, jammers interfere with the IoT MANET communication resulting in order to degrade network performance in terms of delay, throughput and PDR (Packet Delivery Rate) which are the important QoS (Quality of Service) parameters to measure the network performance. The IoT ad hoc system's networking is based on MANET routing protocols so that (GRP, AODV and OLSR) routing protocols had been examined in this paper to improve the QoS (Packet Delivery rate, throughput and delay) of the IoT-MANET system using Riverbed Modeler (17.5) simulation program for different mobile applications. The outcomes showed that the selection of a suitable routing protocol would improve the degradation in delay, throughput and PDR of the ad hoc network.

Next‐generation energy‐efficient optical networking: DQ‐RGK algorithm for dynamic quality of service and adaptive resource allocation

SummaryIn green optical networking, designing an adaptive energy‐saving scheme plays a vital role, in optimizing energy consumption by dynamically adjusting resources based on network traffic and environmental conditions, to a more sustainable and efficient optical communication infrastructure. Traditional methods in optical networking face challenges such as static resource allocation, limited adaptability, inefficient power usage, environmental insensitivity, and scalability issues. Therefore this article proposed a novel method named Dynamic Quality of Service based Random update Genghis Khan (DQ‐RGK) algorithm, the proposed model can tackle the abovementioned complexities. In this study, cluster head dynamic placement is utilized to optimize the network's performance by adapting the placement of cluster heads to the current topology, load distribution, and energy levels in the network nodes. Additionally, Dynamic Quality of Service (QoS) is employed to respond dynamically to changes in network conditions, adapting to varying traffic patterns and resource availability. In this work, the Genghis Khan Shark optimization with a random update strategy is implemented for hyperparameter optimization to enhance the performance of the DQ‐RGK method. The DQ‐RGK adjusts the parameters of QoS in real‐time, and this ensures that network resources based on the requirements changed and priorities of applications, which ultimately optimizes performance and enhances user experience. By dynamically assigning and reallocating resources based on the current demand the algorithm enhances overall network efficiency and reduces energy consumption. Then, this work analyzes the experimental results, where some evaluation measures estimate the DQ‐RGK method's performance. Routing efficiency, latency, scalability, spectral efficiency, Packet Delivery Ratio, throughput, network lifetime, energy consumption, jitter, and energy consumption are the measures employed by the DQ‐RGK model. In The results, other routing models that do not provide efficiency are utilized, a comparison of these other routing models is represented in results. The overall DQ‐RGK model's effectiveness is represented in the experimental results and its effectiveness is greater among other methods.

Latency and Residual Energy Analysis of MIMO Heterogeneous Wireless Sensor Networks

Energy-constrained Wireless Sensor Networks (WSNs) have garnered significant research interest in recent years. Multiple-Input Multiple-Output (MIMO), or Cooperative MIMO, represents a specialized application of MIMO technology within WSNs. This approach operates effectively, especially in challenging and resource-constrained environments. By facilitating collaboration among sensor nodes, Cooperative MIMO enhances reliability, coverage, and energy efficiency in WSN deployments. Consequently, MIMO finds application in diverse WSN scenarios, spanning environmental monitoring, industrial automation, and healthcare applications. This research paper presents a comparative performance analysis of MIMO wireless sensor networks and traditional wireless sensor networks without MIMO using Network Simulator NS2.35 for analysis of End to End Delay for packet transmission and Residual energy of nodes. The research work shows application of MIMO in Wireless Sensor Networks with considerable improvements in Quality of Service parameters which is achieved through Spatial Multiplexing and Diversity Gain. MIMO enables multiple spatial streams, allowing several data streams to be transmitted simultaneously on the same channel. This increases the overall throughput as multiple sensors can transmit their data concurrently without interference. MIMO systems also provide diversity gain by transmitting multiple copies of the same data over different antennas which helps in mitigating the effects of fading and interference, resulting in a more reliable and higher-throughput communication link as compared to a SISO channel. Another advantage of employing MIMO in WSN is reduction in End-to-End delays in data transmission. Last but not the least, MIMO can be configured to optimize the power consumption of individual sensors by adjusting the number of antennas used and transmission power levels based on channel conditions. Hence, MIMO can help to extend the network's lifetime by conserving energy in resource-constrained sensor nodes by preservation of Residual Energy.

Performance and QoS Assessment in WSN: Comparative Analysis of MBC, ECHERP, and PDCH Routing Methods

Objective: The objective of this research is to assess the performance and Quality of Service (QoS) provided by PDCH when compared with ECHERP and MBC routing protocols(RPs) within Wireless Sensor Networks (WSNs). Methods: Utilizing the NS2 Simulator, this paper provides an in-depth exploration of three hierarchical RPs viz. Equalized Cluster Head Election RP (ECHERP), Mobility Based Clustering (MBC), and PDCH (PEGASIS with Double Cluster head). A thorough examination of each protocol's performance is conducted, focusing on a range of QoS metrics such as Energy Consumption, Packet Drop Ratio, Throughput, and Delay. Findings: A comparative assessment is conducted between PDCH, ECHERP, and MBC, extracting QoS parameters. The examination and findings reveal that PDCH exhibits superior performance over ECHERP by 26.15%, 20%, 15.71%, and 37.73%. Similarly, PDCH outperforms MBC by 23.19%, 14.29%, 4.87%, and 15.13% across the mentioned parameters. Novelty: In this simulation, the NS2 software is utilized, with a specific emphasis on the suggested parameters. These metrics are crucial for evaluating the overall performance of different RPs in Wireless Sensor Networks (WSNs).

PSO-Controlled WSN Environment to Mitigate Flooding and Improve Network Lifetime

The Restricted Flooding-based Route Discovery (RFBRD) – Particle Swarm Optimization (PSO) routing scheme introduced for Wireless Sensor Networks (WSNs) in this article not only reduces the energy loss due to unwanted RREQ (Route Request) flooding but also improves the lifetime of the network. Excessive flooding depletes energy and affects the lifetime of the network. Nodes in scarce regions are allowed to forward first and subsequent RREQ packets freely in the network and are relocated using PSO to improve their neighborhood for better neighbor connectivity and coverage. Whereas, nodes in the populated region or dense region are governed by energy ratios and are allowed to forward first RREQ packets only when they satisfy the energy conditions. This scheme is efficient in maintaining a proper balance of QoS (Quality of Service) parameters works well for high-density networks for more than 50 nodes and can restructure network topology obtaining better connectivity. Experimental analysis showed that the performance of AODV is superior in the case of a low-density network (N=40 nodes) while RFBRD-PSO outperforms in all other configurations (60, 80, and 100 nodes). The Packet delivery ratio was increased by 0.08% and the throughput was higher by 11 kbps in the case of RFBRD-PSO. The routing overhead is low by approximately 40% and the average end-to-end delay is found low by 0.04 as compared to the AODV routing. The energy residue in the case of RFBRD-PSO is less than the value of AODV is the cost paid for a higher packet delivery ratio. The neighborhood connectivity is improved by approximately 32%.

Transforming data‐intensive workflows: A cutting‐edge multi‐layer security and quality aware security framework

SummaryThe data‐intensive workflow application executes tasks on edge servers and cloud platforms in a heterogeneous big‐data computing environment. Cloud and edge servers are vulnerable to node attacks and malicious links due to their wireless connections. Thus, detecting and mitigating rogue nodes in edge server communication environments during workflow execution is crucial. In today's workflow execution landscape, there is a rising emphasis on resolving Quality of Service (QoS) and security concerns within homogeneous execution settings. Workflow execution on diverse computing platforms has received limited research. We are developing an edge‐cloud‐specific Multi‐Layer Security and Quality‐Aware (MLSQA) framework to solve research issues in this area. Node attacks are detected via reputation‐based security features in the MLSQA framework, whereas link attacks are detected using machine learning. A unique trade‐off metrics technique optimizes workflow security and QoS parameters, reducing energy usage and makespan. In addition, a fault‐tolerant, energy‐efficient job offloading technique is described in detail to improve the system's resilience to errors. The experiment is conducted using complex (i.e., memory and CPU intensive) scientific procedures with intermediate job dependencies, namely Inspiral workflow. The MLSQA framework excels in threat detection, demonstrating lower false alarms, reduced energy consumption, and quicker implementation than the recent secure workflow execution architecture.

Improve quality of service for the Internet of Things using Blockchain & machine learning algorithms

The quality of service (QoS) parameters in IoT applications plays a prominent role in determining the performance of an application. Considering the significance and popularity of IoT systems, it can be predicted that the number of users and IoT devices are going to increase exponentially shortly. Therefore, it is extremely important to improve the QoS provided by IoT applications to increase their adaptability. Majority of the IoT systems are characterized by their heterogeneous and diverse nature. It is challenging for these systems to provide high-quality access to all the connecting devices with uninterrupted connectivity. Considering their heterogeneity, it is equally difficult to achieve better QoS parameters. Artificial intelligence-based machine learning (ML) tools are considered a potential tool for improving the QoS parameters in IoT applications. This research proposes a novel approach for enhancing QoS parameters in IoT using ML and Blockchain techniques. The IoT network with Blockchain technology is simulated using an NS2 simulator. Different QoS parameters such as delay, throughput, packet delivery ratio, and packet drop are analyzed. The obtained QoS values are classified using different ML models such as Naive Bayes (NB), Decision Tree (DT), and Ensemble, learning techniques. Results show that the Ensemble classifier achieves the highest classification accuracy of 83.74 % compared to NB and DT classifiers.

Advancing Wireless Sensor Networks through Performance Evaluation of M-PDCH Routing Protocol for Enhanced Quality of Service

Objective: The decisive aim of this investigation is to improve the capabilities and limitations of PEGASIS with Double Cluster Head (PDCH), for enhancing the overall Quality of Service (QoS) in Wireless Sensor Networks (WSNs). Methods: This research is intended at the application of efficient routing protocol for wireless sensor networks. It works on the principle of the formation of cluster head and clustering. This is accomplished to achieve high QoS for WSN. Improving the efficacy of a WSN protocol is decisive for optimizing communication, resource utilization, and overall effectiveness. An innovative and novel protocol named Mobile-PDCH (M-PDCH) has been devised, developed, and tested. Here several parameters have been carefully investigated for enhancing the performance of a WSN protocol such as energy consumption, delay, and packet loss. A simulation environment has been created to evaluate, compare, and validate the performance and to suggest the desired applications of the proposed protocol. Findings: In the hierarchical category, PDCH performs better compared to all the other protocols. But it suffers from high packet drop, which decrease the performance of the protocol. To improve the performance of sensor networks, there is a need for adaptive routing protocol. The examination of simulation outcomes for the recommended protocol, M-PDCH, has been conducted in comparison with PDCH. The findings indicate that the protocol exhibits superior performance. The proposed algorithm improves the packet drop by 29.75%, reduces delay by 23.28%, and lowers energy consumption by 19.18% when compared to PDCH. Novelty: A novel adaptive routing protocol termed M-PDCH has been proposed for the enhancement of the WSN life span and durability of the sensor nodes. The simulation results show that the proposed algorithm produces better results compared to PDCH protocol. The various QoS parameter results are compared, verified, and validated with existing protocol PDCH. Keywords: WSN, PDCH, Design issues, Metrics, QoS, HRP

COMPARISON OF QUALITY OF SERVICE PARAMETERS FOR FOUR CELLULAR NETWORK PROVIDERS IN PUNGGUR KECIL VILLAGE

This research aims to analyze Quality of Service (QoS) parameters on cellular networks using four providers by measuring throughput, packet loss, delay and jitter parameters when conducting Video Streaming and Online Games using the Wireshark application. The research method involves direct measurement of QoS parameters in several strategic locations in Punggur Kecil village, data was taken at three different location points with a distance comparison of ±500 meters. From all the recapitulations of QoS parameter measurement results, it can be concluded that the value of each QoS parameter can vary for each package which includes the categories poor, medium, good and very good because the bandwidth received by each provider is different. The cause of high and low values of different QoS parameters, Throughput is caused by the number of packet arrivals measured during the observation process, Packet Loss is caused by the number of queues exceeding capacity, Delay is caused by low Throughput values and the number of packets sent, while the Jitter value is influenced by the Delay value. The results obtained are that the Indosat provider is the recommended provider when carrying out Video Streaming and Online Games, because the Quality of Service value produced is superior to other providers. The average values of the Throughput, Packet Loss, Delay and Jitter parameters at each location for the Indosat provider are respectively 796kbps, 2.63%, 22.6ms and 22.6ms. Provider XL is 708kbps, 1.67%, 12.6ms, and 12.6ms. Provider Telkomsel 667kbps, 0.33%. 55.9ms, and 56ms. As well as the Smartfren provider 50kbps, 0.38%, 102.6ms, and 102.7ms.

Mobile Network Operators’ Assessment Based on Drive-Test Campaign in Urban Area for iPerf Scenario

The development of new telecommunication services requires the implementation of advanced technologies and the next generations of networks. Currently, the Long-Term Evolution (LTE) is a widely used standard. On the other hand, more and more mobile network operators (MNOs) are implementing the fifth-generation (5G) New Radio standard in their networks. It allows for increasing throughput, spectral, and energy efficiency and maximizing coverage, while reducing latency. The effectiveness of the introduced changes is measured by assessing the quality of service (QoS) in mobile networks. The paper presents the result evaluation of the QoS measurement campaign carried out using the drive test method in an urban area for four MNOs. We analyze the data transmission scenario, which is the basis of most modern telecommunications services. The result comparison provides an assessment of the 5G service implementation advancement by MNOs. In this analysis, we consider many QoS metrics (e.g., session time, throughput, and round-trip time) and parameters defining the radio signal quality (i.e., reference signal received power, signal-to-interference-plus-noise ratio). Our work also included searching for relationships between these parameters, using a correlation analysis. It allows for the selection of uncorrelated parameters to assess the quality of network, i.e., MNO evaluation, in terms of the provided QoS.

Performance Analysis of BGP Dynamic Routing Protocol using QOS for TCP and UDP Services

The Border Gateway Protocol (BGP) is commonly used for TCP and UDP services, but it poses challenges in terms of Quality of Service (QoS) analysis. Parameters like throughput, packet loss, delay, and jitter are crucial for assessing network service quality. This study aims to analyze the performance and influence of the BGP routing protocol on TCP and UDP services using QoS parameters. The research used a GNS3 network simulation to conduct multiple packet transmission tests for TCP and UDP protocols, lasting 15, 30, and 60 seconds; and monitored using Wireshark. For TCP services, the average QoS index value is 3.75, categorizing the quality as "Good". The tested network topology and routing configuration exhibit reliable performance, providing good throughput, low packet loss rates, minimal delays, and stable jitter. Similarly, UDP services demonstrate “Good” performance with an average QoS index of 3.75. The BGP routing protocol in the tested network topology ensures high-quality service with good delivery speed, low packet loss rate, minimal delay, and stable jitter. Overall, the study concludes that the BGP routing protocol effectively provides satisfactory QoS for TCP and UDP services. This research contributes to understanding network performance and optimizing routing protocols for improved telecommunications services. The findings highlight the significance of routing protocols in facilitating efficient data transmission on the Internet, reinforcing the importance of QoS analysis for enhancing service quality.