Introduction to Qos Metrics

What is/are Qos Metrics?

Qos Metrics - The proposed model is validated by NS2 simulation and extended to the derivation of other QoS metrics such as packet reception probability, packet reception ratio, and broadcast link capacity, etc. ^[1] In this research paper, an effort has been made to investigate the impact of secure neighborhood on energy consumption and QoS metrics of Dynamic MANETs On-Demand (routing protocol) (DYMO) in MANETS. ^[2] While identifying the candidate routes along with the QoS metrics, heuristic factors and reliable fitness functions are also considered. ^[3] Finally, the machine learning approaches are discussed in the light of QoS metrics to enhance the overall performance of the network. ^[4] Background knowledge on IoT, QoS metrics, and critical enabling technologies will be given beforehand, delving into the literature review. ^[5] The effectiveness of the proposed model is then further investigated by comparing the QoS metrics of the data offloading process with those obtained in a previous study on mobile data offloading under the assumption of a constant bandwidth. ^[6] Hence, using different open-source tools we propose a simplified approach to measure those QoS metrics for publicly available web services. ^[7] Here we have considered initiating time of the packet when transaction starts, also route stability factor and bandwidth inclusion, which are mainly the concern of QoS metrics. ^[8] can cause high variability in these QoS metrics on 4G/LTE, and WiFi networks, which can be detrimental to the application QoE. ^[9] This paper proposes a hybrid approach that combines Stretch with the Hill-climbing method to improve both the throughput and the QoS metrics of the SMT processor. ^[10] The analysis of QoS metrics are validated by NS2 simulation. ^[11] In this work, we have discussed the important characteristics of fog computing frameworks and identified various issues related to its architectural design, QoS metrics, implementation details, applications and communication modes. ^[12] The main challenge we study is to find how the relay node must share its energy between two sources to optimize their QoS metrics, i. ^[13] The factors include Buffer size, Beacon Interval, Back-off-transmission has an ideal impact on QoS metrics in IEEE 802. ^[14] This paper proposed optimal cloud service provider selection (OCSPS) based on QoS metrics. ^[15] The available capacity with the QoS metrics such as throughput, packet loss, and end to end delay are investigated for an optimal cell selection. ^[16] While identifying the candidate routes along with the QoS metrics, heuristic factors and Reliable Fitness Functions are considered. ^[17] The target geometrical localization error and probability of detection are considered as QoS metrics of the network. ^[18] It is shown that the ML method has achieved several benchmarks in terms of QoS metrics for different optimization models. ^[19] Since these loads are usually on/off type, cycling rate is one of their QoS metrics; frequent cycling between on and off states is detrimental to them. ^[20] In this work, we propose safety messages dissemination protocol based on QoS metrics as delay, link quality and flow for the choice of a reliable, fast and efficient broadcaster. ^[21] The proposed scheme is simulated on Cloudsim with different data centre configurations and experimental results are evaluated based on QoS metrics. ^[22] For instance, services like Facebook, Twitter and Netflix continuously gather data from the end users for a variety of analytical purposes such as finding the popular web content amongst their users or monitoring the QoS metrics. ^[23] More so, the intrinsic characteristics of the routing protocols regarding the QoS metrics and transport connection are studied. ^[24] This article analyzes the QoS metrics of a real and emulated SDN network for one of the videostreaming services such as the television over the IP protocol (IPTV). ^[25] The results show the efficiency of the context and the QoS metrics, and that these metrics are applicable and provide relative reliability to the context. ^[26] A mobile broadband performance measurement application (MBPerf) was developed using Java and Extensible Markup Language (XML) and installed on volunteers’ Android Smartphones to measure and collect data relating to 4 (four) QoS metrics – download and upload speeds, latency and DNS (Domain Name Service) lookup; and user data such as mobile phone information, network information, and location information. ^[27] We design a framework for HPC Shelf that employ cloud elasticity concepts for keeping the values of QoS metrics of parallel computing systems inside an acceptable range, enabling adaptations to fulfill the QoS contract restrictions. ^[28] In this paper, we provide state-of-the-art work to evaluate and analyze the QoS metrics in real-time services. ^[29] The evaluation of these algorithms is based on energy and QoS metrics. ^[30] The QoS criteria here are based on the two categories of metrics: QoS metrics and mobility metrics. ^[31] In this paper malicious behavior of Blackhole attack and Rushing attack is studied and analyzed for QoS metrics. ^[32] Introduction -- Emerging Imaging Technologies: Trends and Challenges -- 3D Content Acquisition and Coding -- Efficient Depth-Based Coding -- Error Concealment Methods for Depth Maps -- Light Field Image Compression -- 3D Video Delivery Systems and Tools -- QoE and Qos Metrics for 3D Content -- 3D Visual Content Datasets -- Trans-disciplinary Aspects and Next Generation of 3D Technologies. ^[33] Femtocell deployment is an important strategy when it comes to improvement of QoS metrics in areas of poor cell coverage like indoors in an LTE environment. ^[34] In this paper, closed formulas are provided through the expected utility paradigm to set the insurance premium under different outage models and QoS metrics (no. ^[35] The QoS metrics were measured at three RSUs, averaged over a 2-min period with 0. ^[36] The experimental results confirms that measured performance of the proposed model is highly accurate while it takes into account the percentiles on the QoS metrics. ^[37] The proposed technique is capable of exhibiting superior performance with respect to the baseline method in terms of QoS metrics like throughput and communication overhead. ^[38] It is based on a topology-distance algorithm developed by one of the authors to optimize latency and other QoS metrics. ^[39] We first propose a flexible coexistence framework using the listen-before-talk mechanism, based on which the QoS metrics of LAA-LTE and WiFi systems are quantified. ^[40] This paper aims to analyse the QoS metrics of cloud services based on user satisfaction, and proposes Fairness-based Heuristic Workflow Scheduling and Placement (FHWSP) algorithm with the new multi-objective function. ^[41]

simulation results demonstrate

Moreover, extensive simulation results demonstrate that our proposed routing strategy is able to improve the traffic’s QoS metrics, such as the packet loss ratio and queueing delay. ^[1] The obtained simulation results demonstrate that MDC-LEACH-K had a considerable impact on energy consumption and QoS metrics. ^[2] The obtained simulation results demonstrate that MDC-K improves the energy consumption and QoS metrics compared to LEACH, LEACH-K, MDC maximum residual energy leach, and TEEN protocols. ^[3]

Variou Qos Metrics

Consequently, various QoS metrics in Physical/MAC/Application layer of VANETs are defined and evaluated. ^[1] We measured various QoS metrics Throughput, Jitter, Latency, Loss Ratio and Mean Observed Score (MOS) using an Extended Service Set (ESS) testbed with IPv4 and IPv6 as network layer protocols. ^[2] This entails analysis of various QoS metrics (such as bandwidth, packet loss and jitter) in order to be able to improve their services. ^[3] The result shows that the proposed method is effective through various QoS metrics like overall throughput, packet loss, energy consumption, trust level, false acceptance rate and missed detection rate. ^[4]

Different Qos Metrics

, price), then compositing them to accomplish a complex task to meet users' QoS requirements, where each edge service may have multiple functionally equivalent, but different QoS metrics. ^[1] The diversity of quality-of-service (QoS) necessities of Internet applications prompts several QoS routing techniques which receive different QoS metrics into deliberation. ^[2] Supervised machine learning is a method to predict a class for labeled data, to improve different QoS metrics of several scopes such as educational, industrial and medical etc. ^[3]

Improving Qos Metrics

In this paper, the factor, similarity measure, is introduced and used to find the best cloud and composition plan in each phase which in addition to improving QoS metrics propounded in previous papers, it caused improving QoS metric of load balancing between clouds, prevention of formation of a bottleneck in clouds entrance. ^[1] In this paper we use the factor, similarity measure, to find the most suitable cloud and composition plan in each phase which in addition to improving QoS metrics propounded in previous papers, it caused improving QoS metric of load balancing between clouds, prevention of formation of bottleneck in clouds entrance, decreasing the probability of temporarily failing of any of clouds and consequently increasing the users’ satisfaction. ^[2]

qos metrics propounded

In this paper, the factor, similarity measure, is introduced and used to find the best cloud and composition plan in each phase which in addition to improving QoS metrics propounded in previous papers, it caused improving QoS metric of load balancing between clouds, prevention of formation of a bottleneck in clouds entrance. ^[1] In this paper we use the factor, similarity measure, to find the most suitable cloud and composition plan in each phase which in addition to improving QoS metrics propounded in previous papers, it caused improving QoS metric of load balancing between clouds, prevention of formation of bottleneck in clouds entrance, decreasing the probability of temporarily failing of any of clouds and consequently increasing the users’ satisfaction. ^[2]