Adaptive QoS-Aware Link Scheduling for Scalable and Interference-Constrained Wireless Networks

Department of ECE, BGS Institute of Technology, Adichunchanagiri University BG Nagara, Mandya District, India

^* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

Strong Quality of Service (QoS) assurance is necessary in contemporary wireless networks due to the fast growth of data-intensive and low-latency applications, such as live video streaming, industrial automation, and IoT-based smart systems. However, obtaining consistent communication performance is severely hampered by interference-limited environments, dynamic topologies, and dense deployments. This paper suggests an Adaptive QoS-Aware Link Scheduling (AQLS) framework for scalable and interference-constrained wireless networks as a solution to these problems. The proposed approach models the network using a conflict graph and formulates the scheduling process as an Integer Linear Programming (ILP) problem that simultaneously considers QoS priorities and interference constraints. To ensure real-time applicability, adaptive heuristic and learning-based approximations are introduced to efficiently approximate near-optimal scheduling decisions. Simulation results using NS-3 and MATLAB demonstrate that AQLS performs significantly better than greedy schemes and traditional TDMA in terms of throughput, end-to-end delay, packet delivery ratio, and fairness. Because it achieves a special balance between optimization accuracy, scalability, and QoS adaptability, the proposed framework is a strong candidate for 5G/6G, automotive, and large-scale IoT communication systems.