Bayesian auction game theory-based DBA for XG symmetrical PON

摘要

The next-generation passive optical networks (NG-PONs) (i.e., 50G-PON and Time-division-multiplexing/Wavelength-division-multiplexing, TWDM-PON) offer very high bandwidth with improved quality of service. In these PONs, the role of efficient Dynamic bandwidth allocation (DBA) becomes even more important in reducing the upstream delays, bandwidth waste and reducing the upstream delays and delay variance. These qualities of service metrics lead to improved Quality of Experience (QoE) for the end-users in addition to increased revenue for the service providers. This study introduces the game theory concept in the bandwidth distribution process in PON. Specifically, the Bayesian auction game theory (BAGT) process is used in the DBA process to address the unfair and inefficient distribution of upstream bandwidth to the optical network units (ONUs) in XG symmetrical PON(XGs-PON). The proposed BAGT scheme allocates the excess bandwidth to the entire ONUs in proportion to their demands reported via the bidding process. To validate the performance of the BAGT scheme, we also compare it with other existing DBA schemes namely; proportional allocation schemes (PAS), improved bandwidth utilization (IBU), and optimized round-robin (ORR) methods. The simulation results show that the proposed scheme results in higher system throughput and lower upstream delays than the other schemes. BAGT DBA also improves the bandwidth utilization by up to 38% to 50% compared to IBU, ORR, and PAS schemes and exhibits the minimum frame loss ratio.