Traffic Engineering and Traffic Monitoring in the Case of Incomplete Information

Kodai SATAKE; Tatsuya OTOSHI; Yuichi OHSITA; Masayuki MURATA

doi:10.1587/transcom.2018EBP3049

Traffic Engineering and Traffic Monitoring in the Case of Incomplete Information

Kodai SATAKE, Tatsuya OTOSHI, Yuichi OHSITA, Masayuki MURATA

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Traffic engineering refers to techniques to accommodate traffic efficiently by dynamically configuring traffic routes so as to adjust to changes in traffic. If traffic changes frequently and drastically, the interval of route reconfiguration should be short. However, with shorter intervals, obtaining traffic information is problematic. To calculate a suitable route, accurate traffic information of the whole network must be gathered. This is difficult in short intervals, owing to the overhead incurred to monitor and collect traffic information. In this paper, we propose a framework for traffic engineering in cases where only partial traffic information can be obtained in each time slot. The proposed framework is inspired by the human brain, and uses conditional probability to make decisions. In this framework, a controller is deployed to (1) obtain a limited amount of traffic information, (2) estimate and predict the probability distribution of the traffic, (3) configure routes considering the probability distribution of future predicted traffic, and (4) select traffic that should be monitored during the next period considering the system performance yielded by route reconfiguration. We evaluate our framework with a simulation. The results demonstrate that our framework improves the efficiency of traffic accommodation even when only partial traffic information is monitored during each time slot.

Publication: IEICE TRANSACTIONS on Communications Vol.E102-B No.1 pp.111-121

Publication Date: 2019/01/01

Publicized: 2018/07/23

Online ISSN: 1745-1345

DOI: 10.1587/transcom.2018EBP3049

Type of Manuscript: PAPER

Category: Network

Authors

Kodai SATAKE
  Osaka University
Tatsuya OTOSHI
  Osaka University
Yuichi OHSITA
  Osaka University
Masayuki MURATA
  Osaka University

Keyword

traffic engineering, traffic monitoring, incomplete information, Bayesian Brain

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Kodai SATAKE, Tatsuya OTOSHI, Yuichi OHSITA, Masayuki MURATA, "Traffic Engineering and Traffic Monitoring in the Case of Incomplete Information" in IEICE TRANSACTIONS on Communications, vol. E102-B, no. 1, pp. 111-121, January 2019, doi: 10.1587/transcom.2018EBP3049.
Abstract: Traffic engineering refers to techniques to accommodate traffic efficiently by dynamically configuring traffic routes so as to adjust to changes in traffic. If traffic changes frequently and drastically, the interval of route reconfiguration should be short. However, with shorter intervals, obtaining traffic information is problematic. To calculate a suitable route, accurate traffic information of the whole network must be gathered. This is difficult in short intervals, owing to the overhead incurred to monitor and collect traffic information. In this paper, we propose a framework for traffic engineering in cases where only partial traffic information can be obtained in each time slot. The proposed framework is inspired by the human brain, and uses conditional probability to make decisions. In this framework, a controller is deployed to (1) obtain a limited amount of traffic information, (2) estimate and predict the probability distribution of the traffic, (3) configure routes considering the probability distribution of future predicted traffic, and (4) select traffic that should be monitored during the next period considering the system performance yielded by route reconfiguration. We evaluate our framework with a simulation. The results demonstrate that our framework improves the efficiency of traffic accommodation even when only partial traffic information is monitored during each time slot.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2018EBP3049/_p

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@ARTICLE{e102-b_1_111,
author={Kodai SATAKE, Tatsuya OTOSHI, Yuichi OHSITA, Masayuki MURATA, },
journal={IEICE TRANSACTIONS on Communications},
title={Traffic Engineering and Traffic Monitoring in the Case of Incomplete Information},
year={2019},
volume={E102-B},
number={1},
pages={111-121},
abstract={Traffic engineering refers to techniques to accommodate traffic efficiently by dynamically configuring traffic routes so as to adjust to changes in traffic. If traffic changes frequently and drastically, the interval of route reconfiguration should be short. However, with shorter intervals, obtaining traffic information is problematic. To calculate a suitable route, accurate traffic information of the whole network must be gathered. This is difficult in short intervals, owing to the overhead incurred to monitor and collect traffic information. In this paper, we propose a framework for traffic engineering in cases where only partial traffic information can be obtained in each time slot. The proposed framework is inspired by the human brain, and uses conditional probability to make decisions. In this framework, a controller is deployed to (1) obtain a limited amount of traffic information, (2) estimate and predict the probability distribution of the traffic, (3) configure routes considering the probability distribution of future predicted traffic, and (4) select traffic that should be monitored during the next period considering the system performance yielded by route reconfiguration. We evaluate our framework with a simulation. The results demonstrate that our framework improves the efficiency of traffic accommodation even when only partial traffic information is monitored during each time slot.},
keywords={},
doi={10.1587/transcom.2018EBP3049},
ISSN={1745-1345},
month={January},}

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TY - JOUR
TI - Traffic Engineering and Traffic Monitoring in the Case of Incomplete Information
T2 - IEICE TRANSACTIONS on Communications
SP - 111
EP - 121
AU - Kodai SATAKE
AU - Tatsuya OTOSHI
AU - Yuichi OHSITA
AU - Masayuki MURATA
PY - 2019
DO - 10.1587/transcom.2018EBP3049
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E102-B
IS - 1
JA - IEICE TRANSACTIONS on Communications
Y1 - January 2019
AB - Traffic engineering refers to techniques to accommodate traffic efficiently by dynamically configuring traffic routes so as to adjust to changes in traffic. If traffic changes frequently and drastically, the interval of route reconfiguration should be short. However, with shorter intervals, obtaining traffic information is problematic. To calculate a suitable route, accurate traffic information of the whole network must be gathered. This is difficult in short intervals, owing to the overhead incurred to monitor and collect traffic information. In this paper, we propose a framework for traffic engineering in cases where only partial traffic information can be obtained in each time slot. The proposed framework is inspired by the human brain, and uses conditional probability to make decisions. In this framework, a controller is deployed to (1) obtain a limited amount of traffic information, (2) estimate and predict the probability distribution of the traffic, (3) configure routes considering the probability distribution of future predicted traffic, and (4) select traffic that should be monitored during the next period considering the system performance yielded by route reconfiguration. We evaluate our framework with a simulation. The results demonstrate that our framework improves the efficiency of traffic accommodation even when only partial traffic information is monitored during each time slot.
ER -