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<p>This growing demand for bandwidth-intensive and delay-sensitive applications highlights the critical need for reliable and seamless connectivity in wireless networks. In mobile Wi-Fi environments, frequent and inefficient handoffs caused by fluctuating signal strength (SS) often lead to service interruptions, degraded performance, and inefficient resource utilization. The traditional SS-based handoff schemes have proven insufficient in meeting Quality of Service (QoS) requirements, resulting in unstable and suboptimal network performance. This paper introduces a QoS-aware and symmetry-enhanced handoff management framework for Software Defined Wi-Fi Networks (SDN). The framework integrates two algorithms: Automation-Optimized Handoff (AOH), designed to minimize redundant handoffs using a hysteresis-based SS filtering mechanism, and Reliable and Quality Optimized Handoff (RAQOH), which extends AOH by incorporating additional QoS parameters, such as available bandwidth and Data Loss Rate (DLR), into the handoff decision process. Both algorithms were implemented and evaluated on a hybrid Mininet-NS-3 testbed representing a high-density Wi-Fi scenario. The results demonstrated that RAQOH achieved a 51.85% improvement in throughput, a 37.5% reduction in DLR, and a 6.25% decrease in handoff frequency compared to conventional strategies. Consequently, the proposed framework provides more stable, QoS-driven handoff management, enhancing network utilization and improving user experience in high-mobility wireless environments. To enhance decision flexibility under dynamic wireless conditions, the proposed RAQOH algorithm employs an adaptive Q-score weighting mechanism that adjusts the importance of throughput, delay-loss rate, bandwidth, and signal stability according to real-time network conditions and application type. This adaptive control strengthens QoS preservation during mobility and aligns the framework with emerging SDN-enabled intelligent handoff designs. The proposed framework can be further extended to emerging paradigms such as QoS-aware software-defined Internet of Things (SD-IoT), flow-aware forwarding in SDN data centers, and controller load-balancing optimization, enabling broader applicability across generations of intelligent network systems.</p>

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QoS-Aware Handoff Framework for Performance Optimization in Software-Defined Wi-Fi Networks.

  • 期刊论文

  • 发表日期：

    2026年2月5日

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  • Adnan Nadeem,
  • Ahmed Ali,
  • Nazish Ali,
  • Sohaib Manzoor

摘要

This growing demand for bandwidth-intensive and delay-sensitive applications highlights the critical need for reliable and seamless connectivity in wireless networks. In mobile Wi-Fi environments, frequent and inefficient handoffs caused by fluctuating signal strength (SS) often lead to service interruptions, degraded performance, and inefficient resource utilization. The traditional SS-based handoff schemes have proven insufficient in meeting Quality of Service (QoS) requirements, resulting in unstable and suboptimal network performance. This paper introduces a QoS-aware and symmetry-enhanced handoff management framework for Software Defined Wi-Fi Networks (SDN). The framework integrates two algorithms: Automation-Optimized Handoff (AOH), designed to minimize redundant handoffs using a hysteresis-based SS filtering mechanism, and Reliable and Quality Optimized Handoff (RAQOH), which extends AOH by incorporating additional QoS parameters, such as available bandwidth and Data Loss Rate (DLR), into the handoff decision process. Both algorithms were implemented and evaluated on a hybrid Mininet-NS-3 testbed representing a high-density Wi-Fi scenario. The results demonstrated that RAQOH achieved a 51.85% improvement in throughput, a 37.5% reduction in DLR, and a 6.25% decrease in handoff frequency compared to conventional strategies. Consequently, the proposed framework provides more stable, QoS-driven handoff management, enhancing network utilization and improving user experience in high-mobility wireless environments. To enhance decision flexibility under dynamic wireless conditions, the proposed RAQOH algorithm employs an adaptive Q-score weighting mechanism that adjusts the importance of throughput, delay-loss rate, bandwidth, and signal stability according to real-time network conditions and application type. This adaptive control strengthens QoS preservation during mobility and aligns the framework with emerging SDN-enabled intelligent handoff designs. The proposed framework can be further extended to emerging paradigms such as QoS-aware software-defined Internet of Things (SD-IoT), flow-aware forwarding in SDN data centers, and controller load-balancing optimization, enabling broader applicability across generations of intelligent network systems.