Performance Analysis of Weighted Fair Queuing (WFQ) Scheduler Algorithm through Efficient Resource Allocation in Network Traffic Modeling

Abstract

Bursty traffic patterns require precise classification, modeling, and comprehension to ensure adequate resource allocation, improved network security, and Quality of Service (QoS) assurance. This study introduces a methodology integrating three critical correlation metrics with scheduler algorithms, demonstrating adaptability and improved network performance. Our approach highlights the handling of irregular patterns, contributing to the development of systems that can quickly adapt to changes, significantly enhancing network performance in the context of scheduler algorithms, resource allocation, correlation metrics, and bursty traffic.

Keywords

• quality of service (qos)
• scheduler algorithms
• resource allocation
• correlation metrics
• bursty traffic