Recommendation-Based Bandwidth Calendaring for Packet Transport Network

Shohei KAMAMURA; Rie HAYASHI; Hiroki DATE; Hiroshi YAMAMOTO; Takashi MIYAMURA; Yoshihiko UEMATSU; Kouichi GENDA

doi:10.1587/transcom.2016EBP3126

Recommendation-Based Bandwidth Calendaring for Packet Transport Network

Shohei KAMAMURA, Rie HAYASHI, Hiroki DATE, Hiroshi YAMAMOTO, Takashi MIYAMURA, Yoshihiko UEMATSU, Kouichi GENDA

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This paper proposes a recommendation-based bandwidth calendaring system for packet transport networks. The system provides a user-portal interface with which users can directly reserve packet transport resources. In this regard, the system recommends multi-grade (e.g., multi-price) reservation plans. By adjusting grades of plans in accordance with network resource utilization, this system provides not only reservation flexibility for users but also efficient utilization of network resources. For recommending multi-grade plans, pre-computation of resource allocation is required for every time slot. Because the number of time slots is huge, we also propose an algorithm for fast computation of resource allocation based on time-slot aggregation. Our evaluation suggests that our algorithm can produce a sub-optimal solution within quasi-real time for a large-scale network. We also show that our recommendation-based system can increase the service-provider-revenue in peaky traffic demand environments.

Publication: IEICE TRANSACTIONS on Communications Vol.E100-B No.1 pp.122-130

Publication Date: 2017/01/01

Publicized: 2016/08/04

Online ISSN: 1745-1345

DOI: 10.1587/transcom.2016EBP3126

Type of Manuscript: PAPER

Category: Network

Authors

Shohei KAMAMURA
  NTT Corporation
Rie HAYASHI
  NTT Corporation
Hiroki DATE
  NTT Corporation
Hiroshi YAMAMOTO
  NTT Corporation
Takashi MIYAMURA
  NTT Corporation
Yoshihiko UEMATSU
  NTT Corporation
Kouichi GENDA
  NTT Corporation

Keyword

bandwidth calendaring, packet transport network, recommendation, resource allocation, SDN controller

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Shohei KAMAMURA, Rie HAYASHI, Hiroki DATE, Hiroshi YAMAMOTO, Takashi MIYAMURA, Yoshihiko UEMATSU, Kouichi GENDA, "Recommendation-Based Bandwidth Calendaring for Packet Transport Network" in IEICE TRANSACTIONS on Communications, vol. E100-B, no. 1, pp. 122-130, January 2017, doi: 10.1587/transcom.2016EBP3126.
Abstract: This paper proposes a recommendation-based bandwidth calendaring system for packet transport networks. The system provides a user-portal interface with which users can directly reserve packet transport resources. In this regard, the system recommends multi-grade (e.g., multi-price) reservation plans. By adjusting grades of plans in accordance with network resource utilization, this system provides not only reservation flexibility for users but also efficient utilization of network resources. For recommending multi-grade plans, pre-computation of resource allocation is required for every time slot. Because the number of time slots is huge, we also propose an algorithm for fast computation of resource allocation based on time-slot aggregation. Our evaluation suggests that our algorithm can produce a sub-optimal solution within quasi-real time for a large-scale network. We also show that our recommendation-based system can increase the service-provider-revenue in peaky traffic demand environments.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/transcom.2016EBP3126/_p

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@ARTICLE{e100-b_1_122,
author={Shohei KAMAMURA, Rie HAYASHI, Hiroki DATE, Hiroshi YAMAMOTO, Takashi MIYAMURA, Yoshihiko UEMATSU, Kouichi GENDA, },
journal={IEICE TRANSACTIONS on Communications},
title={Recommendation-Based Bandwidth Calendaring for Packet Transport Network},
year={2017},
volume={E100-B},
number={1},
pages={122-130},
abstract={This paper proposes a recommendation-based bandwidth calendaring system for packet transport networks. The system provides a user-portal interface with which users can directly reserve packet transport resources. In this regard, the system recommends multi-grade (e.g., multi-price) reservation plans. By adjusting grades of plans in accordance with network resource utilization, this system provides not only reservation flexibility for users but also efficient utilization of network resources. For recommending multi-grade plans, pre-computation of resource allocation is required for every time slot. Because the number of time slots is huge, we also propose an algorithm for fast computation of resource allocation based on time-slot aggregation. Our evaluation suggests that our algorithm can produce a sub-optimal solution within quasi-real time for a large-scale network. We also show that our recommendation-based system can increase the service-provider-revenue in peaky traffic demand environments.},
keywords={},
doi={10.1587/transcom.2016EBP3126},
ISSN={1745-1345},
month={January},}

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TY - JOUR
TI - Recommendation-Based Bandwidth Calendaring for Packet Transport Network
T2 - IEICE TRANSACTIONS on Communications
SP - 122
EP - 130
AU - Shohei KAMAMURA
AU - Rie HAYASHI
AU - Hiroki DATE
AU - Hiroshi YAMAMOTO
AU - Takashi MIYAMURA
AU - Yoshihiko UEMATSU
AU - Kouichi GENDA
PY - 2017
DO - 10.1587/transcom.2016EBP3126
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E100-B
IS - 1
JA - IEICE TRANSACTIONS on Communications
Y1 - January 2017
AB - This paper proposes a recommendation-based bandwidth calendaring system for packet transport networks. The system provides a user-portal interface with which users can directly reserve packet transport resources. In this regard, the system recommends multi-grade (e.g., multi-price) reservation plans. By adjusting grades of plans in accordance with network resource utilization, this system provides not only reservation flexibility for users but also efficient utilization of network resources. For recommending multi-grade plans, pre-computation of resource allocation is required for every time slot. Because the number of time slots is huge, we also propose an algorithm for fast computation of resource allocation based on time-slot aggregation. Our evaluation suggests that our algorithm can produce a sub-optimal solution within quasi-real time for a large-scale network. We also show that our recommendation-based system can increase the service-provider-revenue in peaky traffic demand environments.
ER -