Introduction to Qos Enhancement

What is/are Qos Enhancement?

Qos Enhancement - Machine Learning (ML) plays a pivotal role in QoS enhancement, connectivity, and provisioning of smart applications. ^[1] Therefore, we need new protocols that comprehend application behaviours and adapt to dynamic network conditions for more fine-grained QoS enhancement. ^[2] This paper presents a comprehensive survey on various QoS enhancement schemes reported in the literature covering various angles of research domains. ^[3] We conclude that RSMA provides rate, robustness and QoS enhancements over SDMA and NOMA in CoMP JT networks. ^[4] The performance evaluation of the proposed system is conducted and compared with the previous methods to prove the energy efficiency and the QOS enhancements in terms of transmission rate and delay. ^[5] The qualitative and quantitative research demonstrated its viability and replicability in four key points: user acceptance, productivity improvement, QoS enhancement, and fostering of social relations. ^[6] Besides, NSGA-III (Non-dominated Sorting Genetic Algorithm III) is employed to realize the QoS enhancement and ELECTRE (Elimination Et Choix Tradulsant la REaltite) is utilized to solve the decision-making problems of the most optimal scheduling strategies. ^[7] The main contribution of this research is to systematically review researches on QoS enhancement of wireless LAN. ^[8] In this article, we present a novel deep neural network architecture, MV-Net, which provides performance elasticity and contention-aware self-scheduling ability for QoS enhancement in mobile computing systems. ^[9] The experiment results show that our policy outperforms others in combined QoS enhancement, network relaxation and resource utilization. ^[10]