A user application-based access point selection algorithm for dense WLANs.

Area of Science:

• Computer Science
• Wireless Networking
• Network Performance

Background:

• Existing access point (AP) selection schemes often rely on received signal strength, leading to suboptimal performance in various scenarios.
• Alternative methods analyzing AP load can cause significant latency and signaling overhead, especially in dense wireless local area networks (WLANs).

Purpose of the Study:

• To propose a novel AP selection scheme that mitigates latency and signaling overhead in dense WLANs.
• To enhance AP selection by incorporating user application behavior and historical performance data.

Main Methods:

• Developed a user application-based AP selection scheme that monitors application network traffic.
• Estimated achievable AP throughput by analyzing historical performance data without additional signaling.
• Utilized application traffic characteristics to predict AP performance.

Main Results:

• The proposed scheme demonstrated higher throughput compared to existing methods in dense WLAN environments.
• Achieved lower association latency for users in locations with high AP accessibility.
• Effectively predicted AP performance by leveraging application traffic patterns.

Conclusions:

• The user application-based AP selection scheme offers a more efficient and effective approach for dense WLANs.
• This method reduces overhead and improves overall network performance for end-users.
• Historical AP performance data and application traffic analysis are key to optimizing AP selection.