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The expected manifolds increase in the traffic and the massive number of connected Internet of Things (IoT) devices would be a challenge to ensure a certain Quality of Service (QoS) in Beyond 5G (B5G) networks. Due to the increased availability of processing and energy resources and heterogeneous QoS requirements in modern IoT nodes, a client-centric access device selection approach for QoS provisioning in multiple Radio Access Technologies (RATs) scenario is proposed in this paper. The proposed algorithm provides the ability to specify node-specific QoS requirements at each node, a better access device selection, and improved network scalability. For experimental evaluation, a hybrid indoor network consisting of Wireless Fidelity (WiFi) and Light Fidelity (LiFi) RATs has been considered. Experimental results show that the proposed technique outperforms several conventional client-based access device selection approaches by up to 32.66% in network emulation experiments and up to 50% in hardware experimentation. The contribution of this paper includes the proposed algorithm, its complexity and game-theory based convergence analyses, evaluation of the proposed algorithm using network emulation and hardware-based setups, and LiFi channel analysis. The analyses and results imply that the proposed algorithm could be utilized in next-generation IoT networks as it performs better than conventionally used access device selection techniques for QoS provisioning.