Preventive Start-Time Optimization Considering Both Failure and Non-Failure Scenarios

Stephane KAPTCHOUANG; Ihsen AZIZ OUÉDRAOGO; Eiji OKI

doi:10.1587/transcom.2016EBP3370

Preventive Start-Time Optimization Considering Both Failure and Non-Failure Scenarios

Stephane KAPTCHOUANG, Ihsen AZIZ OUÉDRAOGO, Eiji OKI

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This paper proposes a Preventive Start-time Optimization with no penalty (PSO-NP). PSO-NP determines a suitable set of Open Shortest Path First (OSPF) link weights at the network operation start time that can handle any link failure scenario preventively while considering both failure and non failure scenarios. Preventive Start-time Optimization (PSO) was designed to minimize the worst case congestion ratio (maximum link utilization over all the links in the network) in case of link failure. PSO considers all failure patterns to determine a link weight set that counters the worst case failure. Unfortunately, when there is no link failure, that link weight set leads to a higher congestion ratio than that of the conventional start-time optimization scheme. This penalty is perpetual and thus a burden especially in networks with few failures. In this work, we suppress that penalty while reducing the worst congestion ratio by considering both failure and non failure scenarios. Our proposed scheme, PSO-NP, is simple and effective in that regard. We expand PSO-NP into a Generalized Preventive Start-time Optimization (GPSO) to find a link weight set that balances both the penalty under no failure and the congestion ratio under the worst case failure. Simulation results show that PSO-NP achieves substantial congestion reduction for any failure case while suppressing the penalty in case of no failure in the network. In addition, GPSO as framework is effective in determining a suitable link weight set that considers the trade off between the penalty under non failure and the worst case congestion ratio reduction.

Publication: IEICE TRANSACTIONS on Communications Vol.E100-B No.7 pp.1124-1132

Publication Date: 2017/07/01

Publicized: 2017/01/06

Online ISSN: 1745-1345

DOI: 10.1587/transcom.2016EBP3370

Type of Manuscript: PAPER

Category: Internet

Authors

Stephane KAPTCHOUANG
  The University of Electro-Communications
Ihsen AZIZ OUÉDRAOGO
  The University of Electro-Communications
Eiji OKI
  The University of Electro-Communications,Kyoto University

Keyword

link failure, congestion ratio, link weights

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Stephane KAPTCHOUANG, Ihsen AZIZ OUÉDRAOGO, Eiji OKI, "Preventive Start-Time Optimization Considering Both Failure and Non-Failure Scenarios" in IEICE TRANSACTIONS on Communications, vol. E100-B, no. 7, pp. 1124-1132, July 2017, doi: 10.1587/transcom.2016EBP3370.
Abstract: This paper proposes a Preventive Start-time Optimization with no penalty (PSO-NP). PSO-NP determines a suitable set of Open Shortest Path First (OSPF) link weights at the network operation start time that can handle any link failure scenario preventively while considering both failure and non failure scenarios. Preventive Start-time Optimization (PSO) was designed to minimize the worst case congestion ratio (maximum link utilization over all the links in the network) in case of link failure. PSO considers all failure patterns to determine a link weight set that counters the worst case failure. Unfortunately, when there is no link failure, that link weight set leads to a higher congestion ratio than that of the conventional start-time optimization scheme. This penalty is perpetual and thus a burden especially in networks with few failures. In this work, we suppress that penalty while reducing the worst congestion ratio by considering both failure and non failure scenarios. Our proposed scheme, PSO-NP, is simple and effective in that regard. We expand PSO-NP into a Generalized Preventive Start-time Optimization (GPSO) to find a link weight set that balances both the penalty under no failure and the congestion ratio under the worst case failure. Simulation results show that PSO-NP achieves substantial congestion reduction for any failure case while suppressing the penalty in case of no failure in the network. In addition, GPSO as framework is effective in determining a suitable link weight set that considers the trade off between the penalty under non failure and the worst case congestion ratio reduction.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/transcom.2016EBP3370/_p

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@ARTICLE{e100-b_7_1124,
author={Stephane KAPTCHOUANG, Ihsen AZIZ OUÉDRAOGO, Eiji OKI, },
journal={IEICE TRANSACTIONS on Communications},
title={Preventive Start-Time Optimization Considering Both Failure and Non-Failure Scenarios},
year={2017},
volume={E100-B},
number={7},
pages={1124-1132},
abstract={This paper proposes a Preventive Start-time Optimization with no penalty (PSO-NP). PSO-NP determines a suitable set of Open Shortest Path First (OSPF) link weights at the network operation start time that can handle any link failure scenario preventively while considering both failure and non failure scenarios. Preventive Start-time Optimization (PSO) was designed to minimize the worst case congestion ratio (maximum link utilization over all the links in the network) in case of link failure. PSO considers all failure patterns to determine a link weight set that counters the worst case failure. Unfortunately, when there is no link failure, that link weight set leads to a higher congestion ratio than that of the conventional start-time optimization scheme. This penalty is perpetual and thus a burden especially in networks with few failures. In this work, we suppress that penalty while reducing the worst congestion ratio by considering both failure and non failure scenarios. Our proposed scheme, PSO-NP, is simple and effective in that regard. We expand PSO-NP into a Generalized Preventive Start-time Optimization (GPSO) to find a link weight set that balances both the penalty under no failure and the congestion ratio under the worst case failure. Simulation results show that PSO-NP achieves substantial congestion reduction for any failure case while suppressing the penalty in case of no failure in the network. In addition, GPSO as framework is effective in determining a suitable link weight set that considers the trade off between the penalty under non failure and the worst case congestion ratio reduction.},
keywords={},
doi={10.1587/transcom.2016EBP3370},
ISSN={1745-1345},
month={July},}

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TY - JOUR
TI - Preventive Start-Time Optimization Considering Both Failure and Non-Failure Scenarios
T2 - IEICE TRANSACTIONS on Communications
SP - 1124
EP - 1132
AU - Stephane KAPTCHOUANG
AU - Ihsen AZIZ OUÉDRAOGO
AU - Eiji OKI
PY - 2017
DO - 10.1587/transcom.2016EBP3370
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E100-B
IS - 7
JA - IEICE TRANSACTIONS on Communications
Y1 - July 2017
AB - This paper proposes a Preventive Start-time Optimization with no penalty (PSO-NP). PSO-NP determines a suitable set of Open Shortest Path First (OSPF) link weights at the network operation start time that can handle any link failure scenario preventively while considering both failure and non failure scenarios. Preventive Start-time Optimization (PSO) was designed to minimize the worst case congestion ratio (maximum link utilization over all the links in the network) in case of link failure. PSO considers all failure patterns to determine a link weight set that counters the worst case failure. Unfortunately, when there is no link failure, that link weight set leads to a higher congestion ratio than that of the conventional start-time optimization scheme. This penalty is perpetual and thus a burden especially in networks with few failures. In this work, we suppress that penalty while reducing the worst congestion ratio by considering both failure and non failure scenarios. Our proposed scheme, PSO-NP, is simple and effective in that regard. We expand PSO-NP into a Generalized Preventive Start-time Optimization (GPSO) to find a link weight set that balances both the penalty under no failure and the congestion ratio under the worst case failure. Simulation results show that PSO-NP achieves substantial congestion reduction for any failure case while suppressing the penalty in case of no failure in the network. In addition, GPSO as framework is effective in determining a suitable link weight set that considers the trade off between the penalty under non failure and the worst case congestion ratio reduction.
ER -