Dynamic QoS Policy Enforcement and Traffic Shaping Techniques for Next-Generation Mobile Networks

Abstract

In the evolving landscape of next-generation mobile networks, particularly 5G and beyond, ensuring consistent Quality of Service (QoS) across diverse applications remains a significant challenge. Static QoS configurations often fall short in dynamically fluctuating network environments, leading to suboptimal user experiences. This study proposes a dynamic QoS policy enforcement and traffic shaping framework designed to adapt to real-time network conditions and application requirements. The framework utilizes adaptive resource allocation techniques and policy-based traffic prioritization to manage network congestion and ensure service-level differentiation. Performance evaluation is conducted through comparative analysis against traditional static QoS configurations, with a focus on key network performance metrics: latency, throughput, jitter, and packet loss. Simulation results demonstrate the proposed framework’s effectiveness in improving QoS, particularly under high network load and heterogeneous traffic conditions. This research underscores the importance of adaptive policy mechanisms in realizing the full potential of future mobile networks.