Optimization of the Upstream Bandwidth Allocation in Passive Optical Networks Using Internet Users' Behavior Forecast - Archive ouverte HAL Access content directly
Conference Papers Year : 2018

Optimization of the Upstream Bandwidth Allocation in Passive Optical Networks Using Internet Users' Behavior Forecast

Abstract

The application of classification techniques based on machine learning approaches to analyze the behavior of network users has interested many researchers in the last years. In a recent work, we have proposed an architecture for optimizing the upstream bandwidth allocation in Passive Optical Network (PON) based on the traffic pattern of each user. Clustering analysis was used in association with an assignment index calculation in order to specify for each PON user his/her upstream data transmission tendency. A dynamic adjustment of Service Level Agreement (SLA) parameters is then performed to maximize the overall customer's satisfaction with the network. In this work, we extend the proposed architecture by adding a prediction module as a complementary to the first classification phase. Grey Model GM (1,1) is used in this context to learn more about the traffic trend of users and improve their assignment. An experimental study is conducted to show the impact of the forecaster and how it can overcome the limits of the initial model.
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Dates and versions

hal-01760252 , version 1 (02-05-2018)
hal-01760252 , version 2 (30-01-2020)

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Cite

Nejm Eddine Frigui, Tayeb Lemlouma, Stephane Gosselin, Benoît Radier, Renaud Le Meur, et al.. Optimization of the Upstream Bandwidth Allocation in Passive Optical Networks Using Internet Users' Behavior Forecast. ONDM 2018 : 22nd International Conference on Optical Network Design and Modeling, May 2018, Dublin, Ireland. pp.1-6, ⟨10.23919/ONDM.2018.8396107⟩. ⟨hal-01760252v2⟩
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