Bin-packing based offline dynamic bandwidth and wavelength allocation algorithms for power efficiency in Super-PON

Abstract

Enduring the rapidly growing demand for high data rates is the main challenge for the current network providers. Super passive optical network (Super-PON), a prominent next generation Ethernet PON (NG-EPON) candidate, can suffice this exponentially increasing data rate requirements. However, to appease such requirements, it employs many transceivers and increases the power-consumption of the network. In this work, we focus on reducing the carbon footprint of Super-PON and propose power-efficient dynamic bandwidth and wavelength allocation (DBWA) algorithms, namely best fit bin-packing sleep mode aware (BF-SMA) and updated BF-SMA (UBF-SMA). The proposed algorithms use SMA for bandwidth scheduling and different bin-packing techniques for wavelength allocation. In bin-packing, the number of available wavelengths and their efficient allocation is based on the network load. For restricting the number of available wavelengths, we can switch off the non-essential transceivers at the OLT, which also helps in maximizing the wavelength utilization and increasing the power efficiency. The simulation results show that in comparison to the state-of-the-art DBWA algorithms, the proposed algorithms improve the power efficiency and reduce the average delay of a Super-PON system. Furthermore, we use Jain’s fairness index to validate the fairness of the proposed DBWA algorithms.

Dynamic Bandwidth Allocation for C-Band Shared FBG Sensing and Telecommunications

“…Reinforcement learning predictive strategies are investigated to detect fast PON environmental changes [16]. Some dynamic wavelength and DBA algorithms aim to avoid or minimize frame re-arrangement problem when an ONU transmits in multiple TChs [17], or propose sleep mode algorithm based on PON load [18].…”