Intelligent Resource Allocation for Immersive VoD Multimedia in NG-EPON and B5G Converged Access Networks

Immersive content streaming services are becoming increasingly popular on video on demand (VoD) platforms due to the growing interest in extended reality (XR) and spatial experiences. Unlike traditional VoD, immersive VoD (IVoD) offers more engaging and interactive content beyond conventional 2D video. IVoD requires substantial bandwidth and minimal latency to deliver its interactive XR experiences. This research examines intelligent resource allocation for IVoD services across NG-EPON and B5G X-haul converged networks. A proposed software-defined networking (SDN) framework employs artificial neural networks (ANN) with a backpropagation technique to predict bandwidth control based on traffic patterns and network conditions. The new immersive video storage, field-programmable gate array (FPGA), Queue Manager, and logical layer components are added to the existing OLT and ONU hardware architecture to implement the SDN framework. The SDN framework manages the entire network, predicts bandwidth requirements, and operates the immersive media dynamic bandwidth allocation (IMS-DBA) algorithm to efficiently allocate bandwidth to IVoD network traffic, ensuring that QoS metrics are met for IM services. Simulation results demonstrate that the proposed framework significantly enhances mean packet delay by up to 3% and improves packet drop probability by up to 4% as the traffic load varies from light to high across different scenarios, leading to enhanced overall QoS performance.