Introduction to Qos Parameters

What is/are Qos Parameters?

Qos Parameters - Delay, Throughput, Packet Loss, and Packet Delivery are the QoS parameters used in the testing. ^[1] Firstly, QoS parameters are selected and classified according to the network performance and power service demand index; Secondly, the subjective weight and objective weight are obtained respectively based on the analytic hierarchy process and the improved entropy weight method, and the subjective and objective weights are balanced by game theory; Finally, the multi-attribute decision theory is used to select wireless network access which can meet the QoS requirements of power service and the best performance. ^[2] The reliability is an abstraction of QoS parameters like latency, throughput, delay and link utilization which is computed at packet delivery time and captures the motive of other finer QoS parameters. ^[3] This algorithm uses some QoS parameters such as reliability rate, elapsed time to detect impersonation attacks, and stability rate for trust related attacks, to perform an efficient trust calculation of the nodes in communication. ^[4] The performance of the application is to be enhanced by providing Quality of Service (QoS) and the performance is evaluated in terms of QoS parameters like Power utilization, Makespan and Execution Time. ^[5] Thus, the QoS parameters of 5G in Bangkok from this study can be the baseline for the 5G networks that will be used widely in Thailand in the future. ^[6] Mean queue length, throughput and mean response time results for QoS parameters are presented. ^[7] The performances are compared in in terms of QoS parameters, as channel quality, residual energy, link quality, etc. ^[8] An algorithm is proposed for secure communication between source and destination based on the QoS parameters is called Modified Device Key Generation Algorithm (MDKGA). ^[9] Thereafter, for services which do not have enough tags, enrichment of the tag is carried out and finally, using an algorithm, composition solutions based on QoS parameters are extracted, which can formulate user targets or even provide potential compositions. ^[10] In this paper, we aim at providing a characterization of the relationship between QoS parameters and QoE indicators to drive in-network learning and online QoE inference. ^[11] The framework monitors the QoS parameters of traffic flows and identifies policy violations due to link congestion in the network. ^[12] In this work, an approach for web service selection based on QoS parameters is proposed. ^[13] A systematic review is presented in this paper based on QoS parameters in the light of Machine Learning (ML) techniques. ^[14] This trust model generates comprehensive trust value of the data center node based on dynamic trust value combined with QoS parameters. ^[15] In addition, differences on hardware and software specifications also affect the value of QoS parameters. ^[16] The QoS parameters should be prioritised in consideration of MANET constraints and applications running on MANET. ^[17] The performance resulting from the comparison of routing is measured using QoS parameters including the value of throughput, packet loss, delay, and jitter. ^[18] In this paper we focus on security issues and the novel approach for security enhancing the security through evaluation of QoS parameters in IIOT system. ^[19] In the current scenario, to reduce the delay tradeoff when the task is offloading, it requires to examine the QoS parameters that improve the performance of fog computing. ^[20] 5% while decreasing network traffic and power by 15% and 30%, respectively, without affecting other QoS parameters. ^[21] Then a solution, which allows comparison among web-services through the calculation of similarity of the request to amounts of the QoS parameters of available web services, is proposed. ^[22] If congestion in the network is not managed correctly, it can lead to significant loss of QoS parameters, such as decreasing network throughput, increasing energy usage, and decreasing the distribution ratio of packets at the destination or sink node. ^[23] The proposed method improves the performance in data security and QoS parameters. ^[24] Techniques which involve sleep scheduling improve the network lifetime, but reduce other QoS parameters like speed of operation, while techniques involving pre-processing of data guarantees high throughput but increases energy consumption in the network. ^[25] In this paper, we focus on the impact of QoS parameters on MANETs. ^[26] Media transfer or streaming would be virtually impossible if QoS parameters were not used even if the streaming protocols were perfectly designed. ^[27] the proposed system regulates the routing performance based on the QoS parameters, using optimization technique for three hybrid algorithms, named as WLFA- Whale Lion Fireworks optimization algorithm with Fitness Function Routing(FFR) mechanisms. ^[28] Users’ feedback and preferences given to QoS parameters are employed in subjective weight computation. ^[29] The model calculates the overall trust of the devices by using QoS parameters to evaluate the trust of devices through assigned weights. ^[30] The performance of the application is to be enhanced by providing Quality of Service (QoS) and the performance is evaluated in terms of QoS parameters like Power utilization, Makespan and Execution Time. ^[31]

Different Qos Parameters

Moreover the quality of the network is compared using different QoS parameters such as end-to-end delay, throughput, jitter and Mean Opinion Score (MOS). ^[1] We have simulated our proposed model using SUMO and omnet + + simulators and measured performance in terms of success rate of allocation of parking lots and different QoS parameters like packet drop and delay in response. ^[2] The scheduler has to consider the tradeoffs between different QoS parameters in order to satisfy the QoS requirements. ^[3] Resource allocation is an important task by which the user equipment is allocated the required resources based on different QOS parameters. ^[4] To profit from this technology for executing workflow applications, it is necessary to develop workflow scheduling algorithms that consider different QoS parameters such as execution time and cost. ^[5] We discuss the results for the UDP and TCP protocols, and different QoS parameters. ^[6]

Variou Qos Parameters

Subsequently, we classify and summarize the representative work for solving the generalized problems by considering various QoS parameters (e. ^[1] 2 simulation illustrates that enhanced ZRP shows high-performance indexes in various QoS parameters like throughput, End to end delay, Load balancing, Energy consumption, and Delivery ratio concerning existing ZRP. ^[2] So, they suffer from a trade-off between various QoS parameters like network lifetime, energy efficiency, and others. ^[3] In this paper, we have proposed an ant colony optimization-based routing protocol targeting to achieve significant value of various QoS parameters. ^[4] Our comparison is done based on various QoS parameters delay, throughput, packet delivery ratio and false positive detection in the MAC layer. ^[5]

Two Qos Parameters

In this paper, we address the task scheduling problem with the aim of optimizing the time and energy consumption as two QoS parameters in the fog context. ^[1] Many composition models available in the literature compose cloud services based on one or two QoS parameters of the candidate services without considering the complete set. ^[2]

Improve Qos Parameters

Current research focus is to develop mechanisms and protocols that are focused to reduce delays, conserve energy and improve QoS parameters such as Reliability. ^[1] The implemented prioritization mechanism is used to study and improve QoS parameters in Li-Fi networks. ^[2]