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Traffic engineering cooperating with traffic monitoring for the case with incomplete information

机译:信息不完整的交通工程与交通监控配合

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Traffic Engineering (TE) accommodates traffic efficiently by dynamically configuring the routes so as to follow traffic changes. If traffic changes frequently and drastically, the interval to perform the route reconfiguration should be set to a short value, to follow traffic changes. To shorten the interval, obtaining the traffic information becomes a problem; measuring traffic information accurately of the whole network, which is required to calculate the suitable route, is difficult to be obtained in a short interval, due to the overhead to monitor and collect the traffic information. We have proposed the framework of the TE for the case that only a part of traffic information can be obtained at each time slot. This framework was inspired by the human brain mechanism. In this framework the conditional probability is considered to make decisions. In this framework, a controller is deployed. The controller (1) obtains a limited number of traffic information, (2) estimates and predicts the probability distribution of the traffic, (3) configures the routes considering the probability distribution of the predicted future traffic, and (4) selects the traffic to be monitored at the next period considering the performance of the route reconfiguration using the traffic information obtained at the next period. In this paper, we discuss the details of the each step of our framework. Then, we evaluate our framework.
机译:流量工程(TE)通过动态配置路由来跟踪流量变化,从而有效地容纳流量。如果流量频繁且急剧变化,则应将执行路由重新配置的时间间隔设置为较短的值,以跟随流量变化。为了缩短间隔,获取交通信息成为问题。由于监视和收集交通信息的开销,很难在短时间内获得准确测量整个网络的交通信息的能力,这是计算合适的路由所必需的。对于每个时隙只能获取一部分交通信息的情况,我们提出了TE的框架。这个框架是受人脑机制启发的。在这个框架中,条件概率被认为可以做出决定。在此框架中,部署了控制器。控制器(1)获得数量有限的交通信息,(2)估算并预测交通的概率分布,(3)考虑预测的未来交通的概率分布配置路线,并且(4)选择交通以考虑在下一周期使用下一周期获得的业务量信息进行路由重新配置的性能来监视该路由。在本文中,我们讨论了框架每一步的细节。然后,我们评估我们的框架。

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