QoS Parameters Research Articles

Multitopology Routing With Virtual Topologies and Segment Routing

ABSTRACTMultitopology routing (MTR) provides an attractive alternative to segment routing (SR) for traffic engineering when network devices cannot be upgraded. However, due to a high overhead in terms of link state messages exchanged by topologies and the need to frequently update link weights to follow evolving network conditions, MTR is often limited to a small number of topologies and the satisfaction of loose QoS constraints. To overcome these limitations, we propose virtual MTR (vMTR), an MTR extension where demands are routed over virtual topologies that are silent; that is, they do not exchange LSA messages and that are continuously derived from a very limited set of real topologies, optimizing each QoS parameter. In this context, we present a polynomial and exact algorithm for vMTR and, as a benchmark, a local search algorithm for MTR. We show that vMTR helps to reduce drastically the number of real topologies and that it is more robust to QoS changes. In the case where SR can actually be rolled‐out, we also show that vMTR allows to drastically reduce SR overhead.

Optimizing QoS in Wireless Sensor Networks: A Review of Advanced Traffic Control Protocols and Techniques

In wireless sensor network technology (WSNs) the proper congestion processing is the essential key to prevent the parameters of QoS from facing intense loss such as Likelihood of occurrence output reduction and also it may lead to maximize the consumed energy and it also reflect on the increase of the end-to-end time delivery side by side with a noticeable decrease in the percentage of transmitted packet arrival at the destination end. Thus, evolving more superior technology is consider to be one of the most significant challenge in (WSNs) that help to deal with issues like avidness, detection and control in WSNs. This paper review most updated protocols to mitigate the dilemmas of congestion in the WSNs based on the mechanism of congestion’s innate behavior. The protocol categories can be divided into three divisions which are traffic based, resource based and hybrid. The first protocol category (traffic-based) is also witnessed more subdivide based on either the techniques of end-to-end transmission or hop-by-hop. Both the establishment procedure of route and the exploit of active bandwidth techniques. It is also important to indicate that inner operational process of the attenuation linked to congestion protocols are discuss in this paper. Lastly. An intensive study is exploited in this paper to analyze congestion protocols in connection with different performance standards in order to determine which a specific protocol category case is worth to develop. The performance survey shows that the difficulties of accurate detection to the congestion for a particular network if it is only considering the protocols class attitude when it alters with applicable platform and a metric on its own.

AI Based Resource Management for 5G Network Slicing: History, Use Cases, and Research Directions

ABSTRACT5G, 6G, and beyond networks promise to support vertical industrial services with strict QoS parameters, but the hardware‐based "one‐size‐fits‐all" model of legacy networks lacks the flexibility needed for diverse services. The foundation of 5G networks lies in softwarization, with network slicing, Software Defined Networking (SDN), and Network Function Virtualisation (NFV) serving as its core components. The network‐slicing‐based shared network environment necessitates an intelligent and flexible resource management approach. In this case, traditional approaches are no longer suitable for dealing with a dynamic network environment. With recent advancements, AI‐based approaches have the potential to manage resources autonomously. This paradigm shift underscores the need for deep and extensive investigation. However, existing literature on this subject is fragmented and lacks a cohesive overview of network slicing. To address these gaps, our review paper aims to provide a comprehensive scope of network slicing in a unified manner. In this sequence at first, this paper presented a conceptual overview of network slicing and enabling technologies, including SDN, NFV, and edge computing. Secondly, this paper identifies the relevant phases of resource management and presents AI‐based resource management for network traffic classification, admission, allocation, and scheduling. Finally, it also discusses the deployment of network slicing‐enabled key use cases and their practical deployment, the research gap, and open research challenges. To the best of our knowledge, this is the first attempt to critically analyze and present a consolidated review of the state of the art in network slicing resource management modules and network slicing‐enabled key industrial use cases. This paper aims to guide researchers in developing innovative solutions and assist network players in the practical deployment of network slices for industrial applications.

Network Optimization using Real Time Polling Service With and Without Relay Station in WiMAX Networks

IEEE 802.16 can be seen as a compelling replacement for conventional broadband technologies because its primary goal is to provide Broadband Wireless Access (BWA). The variable and uncertain nature of wireless networks makes it much more challenging to ensure QoS in this network. WiMAX Technology is used to support various quality of services which includes UGS, rtps, nrtps, ertps and Best Effort. This study employs an IEEE 802.16 network simulator, which offers adaptable and reliable features for assessing a particular QoS parameters for rtps. Achieving better internet performance in real time services is a challenge now a days, and it is also need of present scenario. This work emphasized on better internet service with good quality of service using rtps with Relay Station and Without Relay Station. In this work the CBR packet size, CBR data rate and data rate with rtps service are fine-tuned for achieving the better performance with good quality of service. When comparing uplink connections in rtps with and without relay station, it is found that the throughput in the uplink is 200% greater when using a relay station. The throughput and goodput are evaluated in uploading and downloading with single and multiple subscriber stations and observed that the multiple subscriber stations in downloading give better performance as compare to single subscriber stations. The throughput and goodput in single subscriber stations is better than multiple subscriber station in uploading. the Academic researchers and commercial developers can use this analysis to validate different WiMAX Network implementation mechanisms and parameters.

Lightweight Cryptography using Pairwise key generation and malicious node detection in large UAV

Data security is very essential concern in network data transmission between various sensor nodes. Data encryption is the only way to provide security to sensitive information during the transmission. Various researchers have developed the different encryption techniques with heterogeneous encryption and decryption keys. Nevertheless, the standard does not include guidance for the administration, storage, or distribution of encryption keys. Various researchers proposed key management techniques, but those methods still generate high overhead during data communication. To eliminate such problems, we suggest lightweight key encryption using pairwise cryptography and malicious node detection from large UAVs. The proposed encryption algorithm compresses the cypher data, reducing the network overhead, and detecting malicious nodes provides higher security from internal and external intruders. In extensive experimental analysis, our simulation obtains better results than existing systems. That enhances around 7-9% throughput with other QoS parameters.

Secured osprey-based energy efficient routing and congestion control in WSN

An adaptive metaheuristic optimization-based QoS-aware, Energy-balancing, Secure Routing Protocol (AQoS-ESRP) is proposed in this article. The network is modelled as a biconcentric hexagon (BiCon-HexA), and the clusters are formed within the BiCon-HexA network. The BiCon-HexA is divided into six sectors to support effective data aggregation, and then clusters are formed within all sectors. The optimal cluster head (CH) selection mechanism is modelled by an Adaptive Hunter-Prey Optimization (AdapH-PO) algorithm considering QoS parameters. Data aggregation is then done securely with an enhanced encryption approach. Here, upgraded elliptic curve cryptography (UEllip-CC) is used to encode data in CH. This UEllip-CC approach provides security improvements in data transmission. Furthermore, in this study, CHs are combined in the multi-hop routing of data packets to reduce the power consumption problems of wireless sensor networks (WSN). To determine the optimal route for data transmission, an energy-balanced multi-path routing algorithm called improved convolutional osprey network (ICON) is presented. Nevertheless, the data transmission nodes can be overloaded in the data routing phase. Here, the congestion problem can be solved by applying an improved version of the Random Early Detection (RED) congestion control model to discard the data packets more noticeably. The simulation of AQoS-ESRP is done with Matlab, and the performance is evaluated using different metrics. When compared to existing systems, the simulation results clearly indicate a significantly higher throughput and delay. Thus, the AQoS ESRP model is employed to maximize the overall data transfer in the WSN.

A Novel Adaptive Random Access Window (RAW) Slot Adjustment Model for IoT Network Using an Integrated Scheme

The RAW (Restricted Access Window) component of the IoT network is deployed to reduce traffic and channel contention in dense and heterogeneous sensor network environment. It divides sensor nodes into groups and slots, allowing channel access only to one RAW slot at a time. Several algorithms and improved channel utilization optimization models have been proposed to optimize the RAW parameters, to ensure a contention free network or at least, minimally reduce it. These techniques often rely on previous traffic demands schedules, collision analysis and send/receive matrices to accurately predict the future of stations’ interactions in an IoT environment. Thus systematically adjusting its operations to reduce contention among the stations and the Access Point(AP), thereby ensuring a flexible transmission even in a dense network environment. This paper critically investigated, analysed and proposed a novel approach to RAW size adjustment. The new approach will invoke data mining instruments and optimisation algorithms to improve performance of stations in an IoT environment and thereafter simulated (with respect to some specified QoS parameters) to ascertain it’s (output) performance index with the already existing models

[formula omitted] : An adaptive data aggregation algorithm for IoT infrastructure

In IoT infrastructure, high-frequency sensing and subsequent transmission of sensed data to computational facilities can lead to redundant data storage and processing, consuming significant storage and processing capacity. As a result, the IoT infrastructure needs more data transmission cycles, leading to data redundancy and low network up-time due to the drainage of limited battery capacity. Conversely, if the data is communicated at a lower rate, it may cause absolute data delivery to the processing unit, which is useless. As a result, a well-designed data aggregation algorithm is required. This paper proposes the ADA2−IoT, an Adaptive Data Aggregation Algorithm for IoT Infrastructure tailored to optimize parameters such as low data redundancy, limited data communication cycles, and high IoT infrastructure up times. The proposed algorithm consists of two key components: the Route Data Aggregator (RDA) performs aggregation during data transit towards the Edge node or gateway, and the Node Data Aggregator (NDA) performs data aggregation during capturing or sensing data. The algorithm employs metrics like Age of Information (AoI) and data freshness factor during the node and route data aggregation phase to capture and timely deliver data to the Edge node, where this data is processed for informed decision-making. The proposed algorithm was efficiently tested on a simulation and IoT hardware deployment environment. Both simulation and hardware results demonstrate a substantial improvement in QoS parameters, such as a decrease in data redundancy and packet exchanges, leading to considerable energy savings and prolonging the lifespan of IoT infrastructure.

Analysis of WiFi Reliability at 2.4 GHz and 5 GHz Frequencies in the Environment of STMIK Sinar Nusantara Surakarta

This research is expected to provide solutions to improve the performance and reliability of the WiFi network at STIMIK Sinar Nusantara, thus supporting teaching and learning activities and enhancing the quality of education. By comparing the quality of WiFi networks between 2.4 GHz and 5 GHz, it aims to shed light on the differences and advantages of each frequency band. Furthermore, the findings of this research can be beneficial for the design of future networks, helping network designers to better understand the importance of frequency management in network infrastructure planning. This research employs an experimental method by testing QoS parameters (throughput, delay, and packet loss) as well as reliability (connection and uptime) at both frequencies. The results of the research indicate that the 5 GHz frequency provides better QoS performance and reliability compared to 2.4 GHz. This research concludes that the 5 GHz frequency could be a solution to improve the WiFi network quality at STIMIK Sinar Nusantara

Optimizing Wireless Sensor Networks through Ant Colony-Based Localized Mesh Topology

The growing need for faster and more effective data handling and data transfer capabilities of a network require energy-efficient and more powerful smart sensor devices. These devices have become increasingly necessary in wireless sensor networks (WSN). The architecture or topology of WSN can greatly impact the organizational efficacy and connectivity among the sensor nodes employed within the given area. It is foremost important to implement a robust network topology which must be capable of ensuring continuous and reliable communication within the whole network. This research paper presents an effective approach based on Ant colony scheme to optimize mesh network topology ant colony optimization (ACO) is used to place the sensor nodes optimally in the given area of the whole network. The proposed research carries out comprehensive performance evaluation of the network under various QoS parameters such as bandwidth, throughput, delay, residual energy and routing load. These parameters shows the effectiveness or adaptability of the network with different and dynamically changing communication requirements suggested by this topology scheme. The network based on the proposed method has been simulated several times and the achieved simulation patterns have been analyzed under the mentioned QoS constraints.

Improved Routing Protocols: A First Step Towards Quality of Service in Mobile Ad-hoc Networks

The recent developments in wireless technology have piqued academics' curiosity. Mobile Adhoc Networks (MANET) is a fast-growing networking architecture used in emergency, disaster, and tactical operations applications. It covers a wide range of applications with some degradation due to its flexible and expandable nature. Because routing is the primary function of wireless networks, routing protocol design is critical in Adhoc networks. Various methods have been used to improve the performance of current routing protocols in different categories. Technical advances in routing protocols have recently been achieved, combined with optimization approaches to improve the overall performance of MANETs routing protocols. This research initially looked at several sorts of routing protocols before going through their variations for energy economy and latency reduction. The previous protocols, which were created utilizing optimization methods, will then illustrate the current requirement. Finally, the review analysis delves into many aspects such as commonly used protocols, optimization techniques, QoS parameters, performance metrics, and future paths. Keywords: MANETs, Energy, Delay, Optimized Protocols, QoS.

A Queue Monitoring System in OpenFlow Software Defined Networks

Real-time trac characteristic is dierent and it is very sensitive to delay. To meet trac specications in real time, monitoring systems are used as an important part of networking. Many monitoring systems are deployed to have an update view of the network QoS parameters and performance. Most of these systems are implemented to measure QoS parameters in links. Here, in this paper, a system for monitoring queues in each link by means of Software Defined Networks is proposed. The monitoring system is implemented by extending Floodlight controller, which uses OpenFlow as southbound protocol. The controller has a centralized view of the network. By the help of OpenFlow it also can provide flow level statistics. Using these advantages, the proposed system can monitor delay and available bandwidth of a queue on a link or path. Despite of monitoring systems in traditional networks, the proposed monitoring system makes a low overhead in network thanks to OpenFlow protocol messages. It is also integrated into the network controller, which enables QoS and trac engineering applications to use the system's reports for automatic trac management and QoS setup. The experimental results show a 99% accuracy of the proposed system for monitoring of both bandwidth and delay.

Rock-hyrax: An energy efficient job scheduling using cluster of resources in cloud computing environment

In a cloud computing environment, job scheduling allows the service provider to schedule resources based on demand. Job scheduling must also ensure QoS, end-user satisfaction, and the efficient usage of resources. Cloud computing vendors assign virtualized computing resources to end-users based on job requirements that are dynamically scalable and pay-per-use. The assignment of jobs requires proper investigation and mapping of available resources. In this paper, we have proposed a novel job scheduling scheme based on Rock Hyrax. Our Rock Hyrax approach uses objective functions to map jobs to available resources. The objective function considers a variety of QoS parameters like makespan, response time and energy efficiency. Our method employs two key QoS parameters: makespan and energy consumption. The node behavior and characteristics, such as processing power, storage, and network connectivity to cluster similar resources, have also been considered for scheduling. An experimental setup is created for a thorough study of the proposal using CloudSim simulator. For both the jobs and virtual machines, static and dynamic scenarios for performance evaluation have been developed. To compare our work with existing scheduling algorithms like ACO, PSO, BFO, and ABC has been considered and we have found that the proposal reduces makespan by 2–9% as increased in jobs. Furthermore, the proposed method reduces total energy consumption in data centers by 7–23% as jobs request increases. The findings support the claim that the proposed method surpasses the existing methods and significantly shortens the time needed to determine the resource required for the job.

Analisis Quality of Service (QoS) Menggunakan Standar Parameter Tiphon pada Jaringan Internet Berbasis Wi-Fi Kampus 1 Unjaya

Internet is a very important need in the life of people in the world. Universities can exchange information and share data and communicate with the internet network. General Achmad Yani University Yogyakarta (Unjaya) uses the internet network for activities that occur on campus. QoS testing or internet network performance aims to maintain the stability of network access on the Unjaya campus and reduce the risk of problems such as delays in data transmission. In addition, this research also aims to determine the results of signal quality measurements in the Unjaya real-time area. In this research, QoS measurement is done by using wireshark application. The QoS parameters measured are throughput, delay, jitter, and packet loss. Based on the measurements taken, the results obtained for QOS measurements show that WiFi network performance based on throughput, delay, jitter, and packet loss parameters is in the good category. The final result obtained after measuring QoS is that the Internet network at Campus 1 Unjaya is in the medium category based on TIPHON standardization with an index value of 3.

The Evolution of Mobile Communication: A Comprehensive Survey on 5G Technology

This comprehensive survey meticulously navigates the evolution of mobile communication, focusing on the revolutionary strides introduced by 5G technology. The study elucidates primary objectives, research methodology, pivotal findings, and implications inherent in the trajectory of mobile communication. It aims for a detailed examination of the technological landscape, outlining features that distinguish 5G from its predecessors. The research methodology involves an exhaustive literature review, culminating in a comprehensive overview of 5G technology. Key findings highlight 5G's transformative capacities, spanning unparalleled data transfer speeds, low-latency communication, and applications like IoT, augmented reality, and autonomous vehicles. The study underscores 5G's far-reaching impact across various sectors. Serving as both a retrospective analysis and a valuable resource, the survey guides researchers, industry professionals, and policymakers through the intricate landscape of 5G technology. Addressing the imperative of accommodating increasing mobile data traffic, the 5G network strives for improved spectrum utilization, energy efficiency, and QoS parameters. Notable innovations include Massive MIMO, promising high spectral efficiency. The focus on efficacy, accuracy, and channel estimation techniques is evident. The article explores specific requirements of 5G wireless communication systems, addressing challenges faced by earlier mobile generations. The advent of 5G emerges as a pivotal solution, aiming for a 1000-fold capacity gain and assuring quality-of-service, higher spectral efficiency, ultra-reliable communication, and facilitating massive machinetype communication. Challenges in traffic load and resource consumption necessitate innovative approaches. The research reviews emerging wireless technologies, including an analysis of Massive MIMO as an efficient solution. The paper promises to be a valuable resource, contributing to the seamless development of state-of-the-art 5G and B5G networks, recognizing the importance of continued research and innovation in the dynamic landscape of mobile communication technologies.

Comparative Analysis of PCC and ECMP Methods in Load Balancing Using GNS3 Simulator

Judging from daily activities, human beings heavily rely on the internet for communication purposes. and exchange information using either social media applications or browsers, vonsistently fast internet speeds are incredibly beneficial for performing tasks and activities, particularly for students and professionals. A sluggish internet connection can be frustrating and may lead to interruptions in online activities and tasks if it persists. Hence, this study examines a comparative evaluation of two approaches, Per Connection Classifier (PCC) and Equal Cost Multi-Path (ECMP) in Load Balancing through GNS3 simulation. Load balancing, as a method for evenly distributing traffic loads, and failover, as a backup mechanism when the main connection experiences problems. GNS3 is a graphical network simulator program that can transmit more complex network topologies compared to other simulators, for example Cisco Packet Tracer. The primary aim of this study is to comprehend how efficiently both techniques distribute traffic loads, maintaining smooth internet access, and increasing reliability. The PCC method produces better throughput, delay and jitter compared to the ECMP method, even though it has slightly different values for each QoS parameter. In testing traffic distribution, the PCC method outperforms the ECMP method. The PCC method can distribute traffic evenly across both ISP lines when downloading and uploading data packets. Meanwhile, the ECMP method can only carry out download and upload activities on one traffic path.

5G Network Coverage Hole Prediction and Detection Using Machine Learning

A signal-free area in a wireless network is called a coverage hole (CH). The signal at this location is either nonexistent or too weak to be detected or monitored. There may sometimes be coverage gaps or places with poor radio frequency (RF) performance due to wireless infrastructure components’ inability to adapt to changing RF dynamics and offer adequate coverage of the locations. Finding coverage gaps and RF problem spots needs a client-side approach rather than the traditional infrastructure-driven solution because of the importance of network intuition. This article’s goal is to locate coverage gaps or weak signal places in a variety of scenarios, including 5G KPIs and QoS parameters (QCI, or quality of service class identifier). The primary objective is to apply classification techniques to determine which use cases or network slices are impacted by the decreased signal strength. Training and test datasets for supervised machine learning techniques are pre-collected measured report data from a live 5G network monitoring counter and data system. Since most KPIs are numerical data, the study uses the classification methods ANN, RF, NB, and LR. This is not at all like the traditional methods—such as driving tests, etc.—for gathering data for coverage-hole detection. Orange Canvas and Microsoft Excel are two instances of data mining technologies that are used for both detection and prediction.

A coherent salp swarm optimization based deep reinforced neuralnet work algorithm for securing the mobile cloud systems

<p>Protecting the mobile cloud computing system from the cyber-threats is the most crucial and demanding problems in recent days. Due to the rapid growth of internet technology, it is more essential to ensure secure the mobile cloud systems against the network intrusions. In the existing works, various intrusion detection system (IDS) frameworks have been developed for mobile cloud security, which are mainly focusing on utilizing the optimization and classification algorithms for designing the security frameworks. Still, some of the challenges associated to the existing works are complex to understand the system model, educed convergence rate, inability to handle complex datasets, and high time cost. Therefore, this research work motivates to design and develop a computationally efficient IDS framework for improving the mobile cloud systems security. Here, an intrinsic collateral normalization (InCoN) algorithm is implemented at first for generating the quality improved datasets. Consequently, the coherent salp swarm optimization (CSSO) technique is deployed for selecting the most relevant features used for intrusion prediction and categorization. Finally, the deep reinforced neural network (DRNN) mechanism is implemented for accurately detecting the type of intrusion by properly training and testing the optimal features. During validation, the findings of the CSSO-DRNN technique are assessed and verified by utilizing various QoS parameters.</p>

PENGARUH PENGGUNAAN VLAN PADA SOFTWARE DEFINED NETWORK BERBASIS RYU CONTROLLER

Software Defined Network (SDN) is a network architecture that separates the control plane and data plane in networking devices, which then makes the control plane independent and programmable. The control plane task is taken by the controller, where the controller can manage all the rules in all networking devices, one type of controller is the Ryu controller. VLAN is a network configuration that distributes several different segments to devices connected to the network that can improve network performance. This study aims to determine the performance of VLAN on Software Defined Network using Ryu Controller using a simulation method with 2 scenarios, namely linear topology 3 OpenFlow Switch 30 hosts and linear topology 3 OpenFlow Switch 60 hosts with traffic of 100, 200, 300, and 400 Mb. Testing is carried out using the rest_router app on the Ryu controller which can run static routing without VLAN and with VLAN so that the difference between using VLAN and not can be seen. The test results show that the linear topology of 3 switches, whether 30 hosts or 60 hosts, can work well. Based on the test of QoS parameters Throughput, Packet Loss, and Jitter, the overall of VLAN is less good than without VLAN, with values of 222.9 Mbps, 0%, 0.0000636 s, and 0.0000675 ms, respectively. However, as the number of hosts increases, VLAN is more reliable.

Multi-Objective Service Composition in Uncertain Environments

Web services have the potential to offer the enterprises with the ability to compose internal and external business services in order to accomplish complex processes. Service composition then becomes an increasingly challenging issue when complex and critical applications are built upon services with different QoS criteria. However, most of the existing QoS-aware service composition techniques are simply based on the assumption that multiple QoS criteria, no matter whether these multiple criteria are conflicting or not, can be combined into a single criterion to be optimized, according to some utility functions. In practice, this can be very difficult as these utility functions or weights are not well-known a priori. In addition, the existing approaches are designed to work in certain environments, where the QoS parameters are well-known in advance. These approaches will render fruitless when facing uncertain and dynamic environments, e.g., cloud environments, where no prior knowledge of the QoS parameters is available. In this paper, two novel multi-objective approaches are proposed to handle QoS-aware Web service composition with conflicting objectives and various restrictions on the quality matrices. The proposed approaches use reinforcement learning in order to deal with the uncertainty characteristics inherent in open and dynamic environments. Experimental results reveal the ability of the proposed approaches to find a set of Pareto optimal solutions, which have the equivalent quality to satisfy multiple QoS-objectives with different user preferences.