Terms Of Quality Of Service Metrics Research Articles

Machine Learning-Driven Ubiquitous Mobile Edge Computing as a Solution to Network Challenges in Next-Generation IoT

Ubiquitous mobile edge computing (MEC) using the internet of things (IoT) is a promising technology for providing low-latency and high-throughput services to end-users. Resource allocation and quality of service (QoS) optimization are critical challenges in MEC systems due to the large number of devices and applications involved. This results in poor latency with minimum throughput and energy consumption as well as a high delay rate. Therefore, this paper proposes a novel approach for resource allocation and QoS optimization in MEC using IoT by combining the hybrid kernel random Forest (HKRF) and ensemble support vector machine (ESVM) algorithms with crossover-based hunter–prey optimization (CHPO). The HKRF algorithm uses decision trees and kernel functions to capture the complex relationships between input features and output labels. The ESVM algorithm combines multiple SVM classifiers to improve the classification accuracy and robustness. The CHPO algorithm is a metaheuristic optimization algorithm that mimics the hunting behavior of predators and prey in nature. The proposed approach aims to optimize the parameters of the HKRF and ESVM algorithms and allocate resources to different applications running on the MEC network to improve the QoS metrics such as latency, throughput, and energy efficiency. The experimental results show that the proposed approach outperforms other algorithms in terms of QoS metrics and resource allocation efficiency. The throughput and the energy consumption attained by our proposed approach are 595 mbit/s and 9.4 mJ, respectively.

Enhancing Modeling for Network Selection Using Graph Theory in Beyond 4G Networks

In recent years, the development and the deployment of different generation systems such as 3G (UMTS, Wi-Fi), 4G (LTE, WIMAX), and 5G have become a reality for different telecommunication operators. At the same time, the development of new mobile devices with multiple interfaces have shifted the behavior of users concerning the utilization of the internet. Additionally, several streaming servers are available to provide real time applications such as e-commerce transactions, video streaming, online gaming, etc. As a result, the users have the privilege to use different multimedia applications at anytime and anywhere. The major trend in Beyond 4G networks is determining the best access network for the end user in terms of quality of service (QoS) during the network selection decision. Thus, in this article, the authors investigate graph theory and the AHP approach to deal with the network selection issue. The experimental results show that the proposed policy can achieve a significant performance in terms of QoS metrics for real-time streaming than conventional algorithms.

An efficient fuzzy logic-based and bio-inspired QoS-compliant routing scheme for VANET

Vehicular ad hoc networks (VANET) are gaining popularity for enabling a wide range of applications for road traffic safety, infotainment and road transportation management. For real-time applications to be successfully deployed in VANET, their quality of service (QoS) requirements need to be met. In this paper, we propose a QoS-based routing protocol named FBQoS-Vanet, which accommodates applications with QoS requirements. This protocol uses a bio-inspired artificial bee colony (ABC) approach for discovering routes complying with QoS criteria. We also use fuzzy logic to identify a feasible path among several available ones discovered by ABC. We rely on the evaluation of a composite fuzzy cost expressed in terms of QoS metrics, where the path must satisfy criteria such as: bandwidth, delay, jitter, and link expiry time. The performance results obtained show the benefits of using our scheme for routing various classes of traffic in VANET with different QoS requirements.

RETRACTED ARTICLE: QoS and QoE Enhanced Resource Allocation for Wireless Video Sensor Networks Using Hybrid Optimization Algorithm

Resource allocation has posed a challenging of scarce resources to activities over time. Problems of optimal resource allocation are motivated by questions that arise in project scheduling, production planning, computer control, broadcasting, routing data, maintenance scheduling, and etc. Data transmission in environmental, security, and health monitoring requires both quality of service (QoS) and quality of equipment (QoE) aware network in order to ensure efficient usage of the resources and effective access. In this paper, we propose a resource allocation scheme for wireless video sensor network using hybrid optimization (RAS-HO) algorithm. Firstly, the cluster formation is performed by the modified animal migration optimization algorithm, which enhances the energy consumption. Secondly, an efficient resource allocation is performed by a glowworm swarm optimization based decision making algorithm. Simulation results show that the proposed scheme achieves required resources better than existing schemes in terms of QoS metrics are energy efficient, delay fairness, throughput, and QoE metrics are peak signal to noise ratio, structural similarity.

Evaluación de Parámetros de QoS en una Red VPN-MPLS Diffserv bajo un Entorno Completo de Emulación de Software Libre

El uso de redes de redes privadas virtuales (VPN-MPLS) se ha vuelto muy común dentro de las empresas gracias a sus múltiples ventajas tales como, la comunicación privada a través de una infraestructura de red pública entre sitios geográficamente diversos. Esto lleva a la necesidad de una red eficiente en términos de calidad de servicio (QoS) para garantizar la fiabilidad y la seguridad de la información. Sin embargo, la implementación de una red VPN-MPLS no es fácil ni económica para las pequeñas y medianas empresas; por lo tanto, en la mayoría de los casos, se requiere usar emuladores que tampoco son gratis. La presente investigación analizó una red VPN-MPLS en términos de métricas QoS: delay, jitter y packet loss. Esta evaluación se realizó en un entorno virtual utilizando sólo herramientas de software libre bajo dos escenarios de prueba, con y sin Servicios Diferenciados (DiffServ). Los resultados mostraron que una red VPN-MPLS DiffServ reduce el delay en aproximadamente 96.78% en VoIP, 39.21% en Datos y 66.83% en Streaming; Además, el jitter se redujo en aproximadamente 27,88% en VoIP y 41,09% en datos.

OpenIPTV: a comprehensive SDN-based IPTV service framework

IPTV is an emerging TV content delivery service that should guarantee Quality of Service (QoS) to deliver television contents over IP for their customers. However, providing such QoS regarding service level agreements (SLA) requires frequent service monitoring and adaptive configuration mechanisms. Nowadays, Software Defined Networks (SDNs) provide capabilities to deploy and manage networks dynamically and can maintain QoS. In this paper, a novel IPTV service framework (OpenIPTV) is proposed, which utilizes SDN as an underlying technology for providing QoS for IPTV customers in a shared backbone network. OpenIPTV is implemented in a well-known OpenDayLight controller and strictly followed a modular design for the sake of efficiency. OpenIPTV comprises all service requirements such as resource monitoring, channel changing, multicast group managing and dynamic QoS multicast traffic engineering. The performance of OpenIPTV is evaluated under different scenarios and experimental results confirmed the effectiveness of the proposed framework in terms of QoS metrics. Furthermore, experimental results show that OpenIPTV is a feasible and practical solution to deliver IPTV services with high level of QoS over SDN.

An Intelligent Traffic Engineering Method over Software Defined Networks for Video Surveillance Systems Based on Artificial Bee Colony

In applications such as video surveillance systems, cameras transmit video data streams through network in which quality of received video should be assured. Traditional IP based networks cannot guarantee the required Quality of Service (QoS) for such applications. Nowadays, Software Defined Network (SDN) is a popular technology, which assists network management using computer programs. In this paper, a new SDN-based video surveillance system infrastructure is proposed to apply desire traffic engineering for practical video surveillance applications. To keep the quality of received videos adaptively, usually Constraint Shortest Path (CSP) problem is used which is a NP-complete problem. Hence, heuristic algorithms are suitable candidate for solving such problem. This paper models streaming video data on a surveillance system as a CSP problem, and proposes an artificial bee colony (ABC) algorithm to find optimal solution to manage the network adaptively and guarantee the required QoS. The simulation results show the effectiveness of the proposed method in terms of QoS metrics.

QoE-Based Performance Evaluation for Adaptive Media Playout Systems

To improve the playout quality of video streaming services, several adaptive media playout (AMP) mechanisms were proposed in literature. However, all performance evaluations and comparisons for AMPs were made in terms of quality of service (QoS) metrics. As one knows, there may exist a trade-off between QoS metrics, such as buffer underflow and overflow performance. Thus, it is not sufficient to only evaluate the performance of AMPs in terms of QoS metrics. In this paper, we will evaluate and compare the performance of several AMPs from the aspect of quality of experience (QoE). Numerical results will show that some existing AMP systems do not perform better than the nonadaptive playout system from the point of view of overall QoE.

Multipath Routing Protocol using Cross-layer based QoS Metrics for IEEE 802. 11e WLAN

To achieve Quality of Service (QoS) support for multimedia traffic, IEEE 802.11e specifies Hybrid Coordination Function (HCF) Controlled Channel Access (HCCA) technique. When it is applied in multi-hop networks, the performance results, however, reveal that there is significant degradation of throughput with high delay at high load conditions. This is due to the fact that routing is responsible for the successful packet delivery and QoS Support. In a single path routing protocol, although multiple paths are discovered by the source during the process of discovering a route, the path with the shortest delay is chosen as the best path while discarding the rest. An increased efficiency can be achieved in terms of QoS metrics, balancing the load and tolerance to faults by the use of multipath routing. Apart from using multipath routing, cross-layer based approach is also necessary for the enhancement of QoS in IEEE 802.11e networks. This paper proposes a multipath routing protocol using cross-layer based metrics for improving the QoS of multimedia traffic in IEEE 802.11e networks. Initially a combined cost metric is formed based on traffic contention time, average transmission delay and signal fading values. The path with minimum combined cost is chosen as the primary path from the multiple disjoint paths discovered. In case of failed data transmission, the traffic is re-routed through an alternate path with next minimum cost. Simulated Performance evaluation substantiates the reliability of the proposed protocol in achieving higher delivery ratio and throughput and reducing the delay. General Terms Average Transmission Delay, Multipath Route Discovery Process, Signal Fading Value, Traffic Contention Time.