A Fuzzy-Hierarchical Algorithm for Proportionally-Fair Rate Allocation to Elastic Users

Pejman GUDARZI; Hossein SAIDI; Farid SHEIKHOLESLAM

A Fuzzy-Hierarchical Algorithm for Proportionally-Fair Rate Allocation to Elastic Users

Pejman GUDARZI, Hossein SAIDI, Farid SHEIKHOLESLAM

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Fairness is one of the most important features of a rate allocation strategy. Proportional fairness criterion has been recently proposed by F. P. Kelly and his colleagues. In this paper, we have proposed a two-level hierarchical technique which allocates proportionally-fair rates to the network elastic users. Part of the network links which are used commonly by the end-users and are congestion prone, constitute the higher (first) level of the hierarchy. In this level, the users with common path in the network are grouped as virtual users. End-users and remaining network links constitute the lower (second) level of hierarchy. To improve the convergence rate of the algorithm, a combination of Jacobi method and fuzzy techniques is deployed in the higher level of hierarchy. Implementing such fast algorithms in the higher level (which is topologically simpler than the whole network), reduces the computational complexity with respect to the use of such algorithms in the whole network. Additionally, the lower level penalty function computation is done once in each N iterations, which reduces the computational complexity furthermore. The simulation results show that the proposed algorithm outperforms that of Kelly in the convergence speed.

Publication: IEICE TRANSACTIONS on Communications Vol.E87-B No.11 pp.3203-3215

Publication Date: 2004/11/01

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Type of Manuscript: PAPER

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Pejman GUDARZI, Hossein SAIDI, Farid SHEIKHOLESLAM, "A Fuzzy-Hierarchical Algorithm for Proportionally-Fair Rate Allocation to Elastic Users" in IEICE TRANSACTIONS on Communications, vol. E87-B, no. 11, pp. 3203-3215, November 2004, doi: .
Abstract: Fairness is one of the most important features of a rate allocation strategy. Proportional fairness criterion has been recently proposed by F. P. Kelly and his colleagues. In this paper, we have proposed a two-level hierarchical technique which allocates proportionally-fair rates to the network elastic users. Part of the network links which are used commonly by the end-users and are congestion prone, constitute the higher (first) level of the hierarchy. In this level, the users with common path in the network are grouped as virtual users. End-users and remaining network links constitute the lower (second) level of hierarchy. To improve the convergence rate of the algorithm, a combination of Jacobi method and fuzzy techniques is deployed in the higher level of hierarchy. Implementing such fast algorithms in the higher level (which is topologically simpler than the whole network), reduces the computational complexity with respect to the use of such algorithms in the whole network. Additionally, the lower level penalty function computation is done once in each N iterations, which reduces the computational complexity furthermore. The simulation results show that the proposed algorithm outperforms that of Kelly in the convergence speed.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e87-b_11_3203/_p

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@ARTICLE{e87-b_11_3203,
author={Pejman GUDARZI, Hossein SAIDI, Farid SHEIKHOLESLAM, },
journal={IEICE TRANSACTIONS on Communications},
title={A Fuzzy-Hierarchical Algorithm for Proportionally-Fair Rate Allocation to Elastic Users},
year={2004},
volume={E87-B},
number={11},
pages={3203-3215},
abstract={Fairness is one of the most important features of a rate allocation strategy. Proportional fairness criterion has been recently proposed by F. P. Kelly and his colleagues. In this paper, we have proposed a two-level hierarchical technique which allocates proportionally-fair rates to the network elastic users. Part of the network links which are used commonly by the end-users and are congestion prone, constitute the higher (first) level of the hierarchy. In this level, the users with common path in the network are grouped as virtual users. End-users and remaining network links constitute the lower (second) level of hierarchy. To improve the convergence rate of the algorithm, a combination of Jacobi method and fuzzy techniques is deployed in the higher level of hierarchy. Implementing such fast algorithms in the higher level (which is topologically simpler than the whole network), reduces the computational complexity with respect to the use of such algorithms in the whole network. Additionally, the lower level penalty function computation is done once in each N iterations, which reduces the computational complexity furthermore. The simulation results show that the proposed algorithm outperforms that of Kelly in the convergence speed.},
keywords={},
doi={},
ISSN={},
month={November},}

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TY - JOUR
TI - A Fuzzy-Hierarchical Algorithm for Proportionally-Fair Rate Allocation to Elastic Users
T2 - IEICE TRANSACTIONS on Communications
SP - 3203
EP - 3215
AU - Pejman GUDARZI
AU - Hossein SAIDI
AU - Farid SHEIKHOLESLAM
PY - 2004
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E87-B
IS - 11
JA - IEICE TRANSACTIONS on Communications
Y1 - November 2004
AB - Fairness is one of the most important features of a rate allocation strategy. Proportional fairness criterion has been recently proposed by F. P. Kelly and his colleagues. In this paper, we have proposed a two-level hierarchical technique which allocates proportionally-fair rates to the network elastic users. Part of the network links which are used commonly by the end-users and are congestion prone, constitute the higher (first) level of the hierarchy. In this level, the users with common path in the network are grouped as virtual users. End-users and remaining network links constitute the lower (second) level of hierarchy. To improve the convergence rate of the algorithm, a combination of Jacobi method and fuzzy techniques is deployed in the higher level of hierarchy. Implementing such fast algorithms in the higher level (which is topologically simpler than the whole network), reduces the computational complexity with respect to the use of such algorithms in the whole network. Additionally, the lower level penalty function computation is done once in each N iterations, which reduces the computational complexity furthermore. The simulation results show that the proposed algorithm outperforms that of Kelly in the convergence speed.
ER -