Traffic Engineering and Traffic Monitoring in the Case of Incomplete Information

Kodai SATAKE  Tatsuya OTOSHI  Yuichi OHSITA  Masayuki MURATA  

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
traffic engineering,  traffic monitoring,  incomplete information,  Bayesian Brain,  

Full Text: PDF>>
Buy this Article

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.