TiWA: Achieving Tetra Indicator Wi-Fi Associations in Software Defined Wi-Fi Networks

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Abstract

With the rise in smart devices, challenges such as traffic management particularly in the indoor scenarios have also increased. Wireless technologies seek to address these needs by using new radio access technologies that offer faster connectivity and access to the Internet. While 4G and 5G provide faster connectivity outdoor, Wi-Fi still remains the dominant technology in indoor scenarios due to its low cost and easy deployment. However, the IEEE 802.11 standard does not address the fairness of load in user-Access point (AP) associations, resulting in unequal user distributions and subpar resource utilization. Densification has been employed in the past to address the aforementioned issue, but it is costly as it requires more hardware. Load balancing is necessary in high-density Wi-Fi networks in order to guarantee quality of service (QoS). To avoid the densification and issues related to load balancing at the APs this paper introduces tetra indicator Wi-Fi associations (TiWA), a combined SDN-based user association and channel assignment solution for Wi-Fi networks. TiWA considers multi-criteria to make better association decisions. The wireless stations from an overloaded OpenFlow enabled AP (OAP) are handed to an underloaded OAP by considering multi-metrics such as the packet loss rate, received signal strength indicator (RSSI), throughput and channel occupancy. Extensive experimentations on 5G EmPOWER platform show that TiWA surpasses previous research methods based on load balancing in terms of aggregated throughput by 39%, offering superior level of load fairness and supporting greater numbers of users and traffic prior to hitting the point at which densification is required.

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APA

Manzoor, S., Kayani, M. A., Ali, N., Ratyal, N. I., & Mohamed, H. G. (2023). TiWA: Achieving Tetra Indicator Wi-Fi Associations in Software Defined Wi-Fi Networks. IEEE Access, 11, 89520–89534. https://doi.org/10.1109/ACCESS.2023.3307476

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