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

S Garg, A Dixit - OSA Continuum, 2021 - opg.optica.org
OSA Continuum, 2021opg.optica.org
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 …
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.
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