Auction-based hybrid DBA algorithm in EPON-WiMAX converge network for 5G and beyond (5 GB) communications

Abstract

Managing large data volumes requires high-capacity networks due to increasing internet users and bandwidth-intensive applications. Optical fiber, particularly Ethernet passive optical network (EPON), is vital for cost-efficient last-mile connectivity. EPON handles data traffic, while WiMAX demands extensive bandwidth due to rising mobile users. Both the networks experience bursty user-generated traffic with fluctuating bandwidth needs. That’s why, the bandwidth requirements of each subscriber fluctuates dynamically. Moreover, access networks must provide distinct service quality to support a large number of users and ensure the requirement of 5G and beyond (5 GB) communication standards. To address these difficulties, in this paper, we propose a prediction-based hybrid dynamic bandwidth allocation (PHDBA) algorithm for EPON-WiMAX converge network. Due to the increasing value of trustworthy network service access, we have implemented a statistical modeling technique. Our technique predicts the heavily loaded ONUs from a randomly generated dataset and provides an approximation of the amount of data that can be strongly loaded. To make this prediction, we have proposed a statistical modeling technique and updated the auction-based semi dynamic bandwidth allocation (SDBA) algorithm. To validate our proposed algorithm, computer simulation is used to evaluate different performance parameters in terms of end-to-end delay, jitter, throughput, and fairness. From the comparative analyses, it is proved that our proposed scheme surpasses the competition over the existing SDBA algorithm.