A New Approach Based on Intelligent Method to Classify Quality of Service

Abstract

Computer networks are used more frequently for time-sensitive applications like voice over internet protocol and other communications. In computer networks, quality of service (QoS) can be crucial since it makes it easier to assess a network's performance and offers mechanisms for enhancing its performance. As a result, understanding the QoS offered by networks is essential for both network users and network service providers in order to assess how well the transmission requirements of different applications are satisfied and to implement improvements to network performance. Next-generation monitoring systems must not only detect network performance deterioration instantly but also pinpoint the underlying cause of quality of service problems in order to achieve strict network standards. A brand-new fuzzy logic-based algorithm is suggested as a solution to this issue. Thus, the proposed approach was evaluated and compared with probabilistic neural networks (PNN) and Bayesian classification as well as network performance measurement, latency, jitter, and packet loss. All approaches correctly classified the QoS categories, although generally, the fuzzy approach outperformed PNN and Bayesian. An improved comprehension of the network performance is acquired by precisely determining its QoS.