IEICE TRANSACTIONS on Communications
Fairness Improvement of Multiple-Bottleneck Flow in Data Center Networks
Summary :
Quantized congestion notification (QCN), discussed in IEEE 802.1Qau, is one of the most promising Layer 2 congestion control methods for data center networks. Because data center networks have fundamentally symmetric structures and links are designed to have high link utilization, data center flows often pass through multiple bottleneck links. QCN reduces its transmission rate in a probabilistic manner with each congestion notification feedback reception, which might cause excessive regulation of the transmission rate in a multiple-bottleneck case because each bottleneck causes congestion feedbacks. We have already proposed QCN with bottleneck selection (QCN/BS) for multicast communications in data center networks. Although QCN/BS was originally proposed for multicast communications, it can also be applied to unicast communications with multiple bottleneck points. QCN/BS calculates the congestion level for each switch based on feedback from the switch and adjusts its transmission rate to the worst congestion level. In this paper, we preliminarily evaluate QCN/BS in unicast communications with multiple tandem bottleneck points. Our preliminary evaluation reveals that QCN/BS can resolve the excessive rate regulation problem of QCN but has new fairness problems for long-hop flows. To resolve this, we propose a new algorithm that integrates QCN/BS and our already proposed Adaptive BC_LIMIT. In Adaptive BC_LIMIT, the opportunities for rate increase are almost the same for all flows even if their transmission rates differ, enabling an accelerated convergence of fair rate allocation among flows sharing a bottleneck link. The integrated algorithm is the first congestion control mechanism that takes into account unicast flows passing through multiple tandem bottleneck points based on QCN. Furthermore, it does not require any modifications of switches used in QCN. Our simulation results show that our proposed integration of QCN/BS and Adaptive BC_LIMIT significantly mitigates the fairness problem for unicast communications with multiple bottleneck points in data center networks.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E99-B No.7 pp.1445-1454
- Publication Date
- 2016/07/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2015EBP3404
- Type of Manuscript
- PAPER
- Category
- Network
Authors
Kenta MATSUSHIMA
Kansai University
Kouji HIRATA
Kansai University
Miki YAMAMOTO
Kansai University
Keyword
Latest Issue
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Kenta MATSUSHIMA, Kouji HIRATA, Miki YAMAMOTO, "Fairness Improvement of Multiple-Bottleneck Flow in Data Center Networks" in IEICE TRANSACTIONS on Communications,
vol. E99-B, no. 7, pp. 1445-1454, July 2016, doi: 10.1587/transcom.2015EBP3404.
Abstract: Quantized congestion notification (QCN), discussed in IEEE 802.1Qau, is one of the most promising Layer 2 congestion control methods for data center networks. Because data center networks have fundamentally symmetric structures and links are designed to have high link utilization, data center flows often pass through multiple bottleneck links. QCN reduces its transmission rate in a probabilistic manner with each congestion notification feedback reception, which might cause excessive regulation of the transmission rate in a multiple-bottleneck case because each bottleneck causes congestion feedbacks. We have already proposed QCN with bottleneck selection (QCN/BS) for multicast communications in data center networks. Although QCN/BS was originally proposed for multicast communications, it can also be applied to unicast communications with multiple bottleneck points. QCN/BS calculates the congestion level for each switch based on feedback from the switch and adjusts its transmission rate to the worst congestion level. In this paper, we preliminarily evaluate QCN/BS in unicast communications with multiple tandem bottleneck points. Our preliminary evaluation reveals that QCN/BS can resolve the excessive rate regulation problem of QCN but has new fairness problems for long-hop flows. To resolve this, we propose a new algorithm that integrates QCN/BS and our already proposed Adaptive BC_LIMIT. In Adaptive BC_LIMIT, the opportunities for rate increase are almost the same for all flows even if their transmission rates differ, enabling an accelerated convergence of fair rate allocation among flows sharing a bottleneck link. The integrated algorithm is the first congestion control mechanism that takes into account unicast flows passing through multiple tandem bottleneck points based on QCN. Furthermore, it does not require any modifications of switches used in QCN. Our simulation results show that our proposed integration of QCN/BS and Adaptive BC_LIMIT significantly mitigates the fairness problem for unicast communications with multiple bottleneck points in data center networks.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2015EBP3404/_p
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@ARTICLE{e99-b_7_1445,
author={Kenta MATSUSHIMA, Kouji HIRATA, Miki YAMAMOTO, },
journal={IEICE TRANSACTIONS on Communications},
title={Fairness Improvement of Multiple-Bottleneck Flow in Data Center Networks},
year={2016},
volume={E99-B},
number={7},
pages={1445-1454},
abstract={Quantized congestion notification (QCN), discussed in IEEE 802.1Qau, is one of the most promising Layer 2 congestion control methods for data center networks. Because data center networks have fundamentally symmetric structures and links are designed to have high link utilization, data center flows often pass through multiple bottleneck links. QCN reduces its transmission rate in a probabilistic manner with each congestion notification feedback reception, which might cause excessive regulation of the transmission rate in a multiple-bottleneck case because each bottleneck causes congestion feedbacks. We have already proposed QCN with bottleneck selection (QCN/BS) for multicast communications in data center networks. Although QCN/BS was originally proposed for multicast communications, it can also be applied to unicast communications with multiple bottleneck points. QCN/BS calculates the congestion level for each switch based on feedback from the switch and adjusts its transmission rate to the worst congestion level. In this paper, we preliminarily evaluate QCN/BS in unicast communications with multiple tandem bottleneck points. Our preliminary evaluation reveals that QCN/BS can resolve the excessive rate regulation problem of QCN but has new fairness problems for long-hop flows. To resolve this, we propose a new algorithm that integrates QCN/BS and our already proposed Adaptive BC_LIMIT. In Adaptive BC_LIMIT, the opportunities for rate increase are almost the same for all flows even if their transmission rates differ, enabling an accelerated convergence of fair rate allocation among flows sharing a bottleneck link. The integrated algorithm is the first congestion control mechanism that takes into account unicast flows passing through multiple tandem bottleneck points based on QCN. Furthermore, it does not require any modifications of switches used in QCN. Our simulation results show that our proposed integration of QCN/BS and Adaptive BC_LIMIT significantly mitigates the fairness problem for unicast communications with multiple bottleneck points in data center networks.},
keywords={},
doi={10.1587/transcom.2015EBP3404},
ISSN={1745-1345},
month={July},}
Copy
TY - JOUR
TI - Fairness Improvement of Multiple-Bottleneck Flow in Data Center Networks
T2 - IEICE TRANSACTIONS on Communications
SP - 1445
EP - 1454
AU - Kenta MATSUSHIMA
AU - Kouji HIRATA
AU - Miki YAMAMOTO
PY - 2016
DO - 10.1587/transcom.2015EBP3404
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E99-B
IS - 7
JA - IEICE TRANSACTIONS on Communications
Y1 - July 2016
AB - Quantized congestion notification (QCN), discussed in IEEE 802.1Qau, is one of the most promising Layer 2 congestion control methods for data center networks. Because data center networks have fundamentally symmetric structures and links are designed to have high link utilization, data center flows often pass through multiple bottleneck links. QCN reduces its transmission rate in a probabilistic manner with each congestion notification feedback reception, which might cause excessive regulation of the transmission rate in a multiple-bottleneck case because each bottleneck causes congestion feedbacks. We have already proposed QCN with bottleneck selection (QCN/BS) for multicast communications in data center networks. Although QCN/BS was originally proposed for multicast communications, it can also be applied to unicast communications with multiple bottleneck points. QCN/BS calculates the congestion level for each switch based on feedback from the switch and adjusts its transmission rate to the worst congestion level. In this paper, we preliminarily evaluate QCN/BS in unicast communications with multiple tandem bottleneck points. Our preliminary evaluation reveals that QCN/BS can resolve the excessive rate regulation problem of QCN but has new fairness problems for long-hop flows. To resolve this, we propose a new algorithm that integrates QCN/BS and our already proposed Adaptive BC_LIMIT. In Adaptive BC_LIMIT, the opportunities for rate increase are almost the same for all flows even if their transmission rates differ, enabling an accelerated convergence of fair rate allocation among flows sharing a bottleneck link. The integrated algorithm is the first congestion control mechanism that takes into account unicast flows passing through multiple tandem bottleneck points based on QCN. Furthermore, it does not require any modifications of switches used in QCN. Our simulation results show that our proposed integration of QCN/BS and Adaptive BC_LIMIT significantly mitigates the fairness problem for unicast communications with multiple bottleneck points in data center networks.
ER -
English
