Global priority DBA using fuzzy logic in Ethernet PON

Radzi, Nurul Asyikin Mohamed; Din, Norashidah Md; Majid, M. S. A.; Al-Mansoori, M. H.

doi:10.1109/apcc.2011.6152770

Cited by 2 publications

(1 citation statement)

References 9 publications

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“…The fuzzy logic methods and tools have also been applied to QoS management for wireless sensors 49,52,17 and adhoc mobile networks 28,43 . Other researchers have developed strategies based on fuzzy logic for congestion control, 5,41,47 traffic smoothing, 31 scheduling policies, 39,45 routing protocols, 34,50 network energy consumption 15 or data distribution in Internet of things 29 . Generally, these studies justify the selection of fuzzy logic because it facilitates an overall grasp of the network complexity.…”

Section: Introductionmentioning

confidence: 99%

Using fuzzy rules for network behavior identification: application for differentiated services in an Ethernet network

Bombardier¹,

Georges²,

Rondeau³

et al. 2018

IJCIS

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The Quality of Service (QoS) offered by a network is based on criteria such as delay, jitter and message loss. QoS management is crucial to ensure that the network respects the communication constraints defined by the application requirements. The network must dynamically manage QoS according to the evolution of network usage. To control QoS, the network implements mechanisms to schedule and regulate traffic. The main issue is identifying the relationship between these mechanisms and their effects on QoS values. The objective of this paper is to propose a method, based on fuzzy logic, for identifying this relationship and reusing it to dynamically control QoS. This study only focuses on the impact of the Weighted Round Robin (WRR) scheduler on the delay in a switched Ethernet network. The fuzzy controller is implemented in a network simulation tool (Riverbed Modeler) to efficiently manage the delay in the network.

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