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Bin-Packing-Based Online Dynamic Bandwidth and Wavelength Allocation Algorithm in Super-PON

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dc.contributor.author Garg, Sukriti
dc.date.accessioned 2024-05-10T11:14:00Z
dc.date.available 2024-05-10T11:14:00Z
dc.date.issued 2021
dc.identifier.uri https://ieeexplore.ieee.org/abstract/document/9562548
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/14815
dc.description.abstract Super passive optical network (Super-PON) is a next-generation Ethernet PON (NG-EPON) candidate that is envisaged to provide high data rate and low latency. For NG-EPON, there are two types of algorithms that manages bandwidth and wavelength scheduling, namely offline and online. The latter method is more scalable and efficient than the former method. Several online algorithms exist that propose schemes to manage wavelength and bandwidth scheduling. However, these algorithms lack in efficient wavelength utilization and switching. In this work, we propose a novel online bin-packing based dynamic bandwidth and wavelength allocation (DBWA) algorithm for Super-PON, namely updated best fit bin-packing (UBF-BP). This algorithm limits the wavelength switching per cycle, and uses the modified version of best fit bin-packing (BF-BP) technique for optimal wavelength allocation. Simulation results show that the proposed DBWA algorithm has a low complexity and overcomes the inefficiencies of wavelength utilization and switching. This results in lower network delay and higher channel utilization than the state-of-the-art DBWA. Furthermore, to verify the correctness of the proposed algorithm, we propose an analytical model and validate these simulation results with the analytical results. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject EEE en_US
dc.subject Bin-packing en_US
dc.subject DBWA en_US
dc.subject Delay Analysis en_US
dc.subject NG-EPON en_US
dc.subject Super-PON en_US
dc.title Bin-Packing-Based Online Dynamic Bandwidth and Wavelength Allocation Algorithm in Super-PON en_US
dc.type Article en_US


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