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d 2,14 vs. rate of added traffic rately as long as the amount of traffic between each node pair varies periodically because Eq. (3) can model any periodic traffic variations by setting N f to a sufficiently large value.
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SUMMARY Obtaining current traffic matrices is essential to traffic en- gineering (TE) methods. Because it is difficult to monitor traffic matrices, several methods for estimating them from link loads have been proposed. The models used in these methods, however, are incorrect for some real networks. Thus, methods improving the accuracy of estimatio...
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We propose an approach which formulates the traffic matrix estima-tion problem as a non-negativity constrained optimization problem, and then a projection method is used to solve it. We conduct experiments both on synthetic and real measurement data obtained from the Abilene network. The results indi-cate that the estimated traffic matrices are mor...
Citations
... Network providers must cost-effectively handle such significant traffic changes. Optical-layer traffic engineering (TE) [1][2][3][4][5][6][7] is one approach for handling traffic changes in a cost-effective manner. In optical-layer TE, in response to the changes of traffic volume in a network, a virtual network topology (VNT) is dynamically configured by setting up optical paths through optical cross-connects. ...
... Juva [9] calculated the range of each traffic demand by using the traffic volume information on each link and optimized the traffic routes to minimize the worst case of link utilization. Roughan et al. [1] and Ohsita et al. [2,3] calculated the VNT and/or the traffic routes by estimating the traffic demand matrices from the traffic volume information on each link. However, these studies are not concerned with the collecting overhead at the centralized server. ...
Traffic information is required to perform optical-layer traffic engineering (TE). However, as the number of nodes in optical networks increases, the overhead for collecting the traffic volume information becomes large. In this paper, we develop a method that reduces the overhead for collecting traffic volume information by selecting a subset of nodes and by only collecting the traffic volume information from the selected nodes. Then, we estimate the traffic volume using the information gathered from the selected nodes. According to the simulation results, we clarify that our method can accurately identify the congested links in real ISP topologies, where the number of traffic demands passing through some links is large; however, the estimation errors of our method become large when the number of traffic demands passing each link is small. Furthermore, optical-layer TE can sufficiently mitigate congestion by using the traffic volume estimated by our method from the information on 50% of all nodes in the case of the Japan topology and 30% of all nodes in the case of the AT&T topology.
... Traffic Engineering (TE) [2][3][4][5][6][7][8] is one efficient way of handling such traffic changes. In the TE, we deploy a server called the Path Computation Element (PCE). ...
... To reduce the amount of information required by the TE, several TE methods using only the information of traffic amount on each link have been proposed [3][4][5][6]. The methods proposed by Refs. ...
... The methods proposed by Refs. [3][4][5] perform the TE by using the traffic amounts between all nodes estimated by the traffic amount on each link. However, there are the cases that the routes calculated by these approaches cannot mitigate the congestions due to estimation errors. ...
Traffic Engineering (TE) is one efficient approach to handle traffic changes. To perform TE, a server called the Path Computation Element (PCE) collects the traffic information from all nodes within the network. Then, the PCE calculates the routes suitable to the current traffic. However, in a large-scale network, it is difficult for one PCE to collect all traffic information in a short period of time. Thus, it takes time to change the routes according to traffic changes. In this paper, we propose a method that changes the routes suitable to the current traffic soon after the traffic changes. In our method, we hierarchically divide the network into multiple ranges; the ranges of the lowest layer are constructed of a small number of nodes and the ranges of the upper layer are constructed from the multiple ranges of the lower layer. We deploy a PCE for each range. The PCEs in the lowest layer change the routes within a small range in a short interval according to the traffic information within the range to handle the traffic changes that occur in a short period of time. Against the traffic change that cannot be handled in the lower layer, the PCEs in the upper layer change the routes within the large ranges of the upper layer according to the aggregated traffic information collected from the PCEs of the lower layer. We also propose a method to aggregate traffic information and a method to calculate the new routes by using the aggregated traffic information considering the upper bounds of link utilizations. In this method, we aggregate traffic information so that we can calculate the upper bounds of the link utilizations after the route change only from the aggregated traffic information. Then, the PCE obtaining the aggregated traffic information calculates the new routes without causing any new congestion by checking the upper bounds of link utilizations calculated from the aggregated traffic information. In this paper, we evaluate our method by simulation and clarify that our method can mitigate the congestion soon after the traffic changes.
... Traffic engineering is a method to optimize the performance of networks by dynamically changing the topology and/or route of traffic [1][2][3][4][5]. The topology and route of traffic are calculated and controlled with a server called Path Computation Element (PCE). ...
... Juva [5] calculates the range of each edge-toedge traffic by using the information of traffic amount on each link, and optimizes the traffic routes that minimize the worst-case link utilization. Roughan et al. [2] and Ohsita et al. [3,4] use the traffic matrices estimated from the information of traffic amount on each link. The traffic amount on a link can be easily counted at the node connected to the link, and the PCE can obtain the information of traffic amount on the link by querying the node. ...
Traffic information is required to perform traffic engineering. However, as the network that require traffic engineering becomes large, the overhead to collect the traffic amount information required for traffic engineering becomes large. In this paper, we propose a method to reduce the over-head to collect the traffic amount information. In our method, we select a subset of nodes and collect the traffic amount information only from the selected nodes. Then, we estimate the traffic amount on each link by using the information collected from the selected nodes. According to simulation results, our method can estimate the traffic amount on each link required for traffic engineering accurately by monitoring 30% of all nodes.
One approach to accommodate a large and time-varying traffic is dynamical routing reconfiguration based on the traffic matrix (TM), which is obtained by monitoring the amounts of traffic between all node pairs. However, it is difficult to monitor and collect the amounts of traffic between all node pairs in a large network. Though reconfiguration methods only based on the amount of traffic on each link have been proposed to overcome this problem, these methods, require a large calculation time and cannot be applied to large networks. This paper discusses a dynamic routing reconfiguration method that can adapt routes to changes in traffic within a short period only based on the amount of traffic on each link. We introduce a hierarchical routing reconfiguration based on the monitored amount of traffic on each link to reduce the calculation time. Moreover, we also propose a method of aggregating traffic information that is suitable for hierarchical routing reconfiguration based on the monitored amount of traffic on each link. Our method aggregates traffic information so that the upper bounds of link utilization after route changes can be calculated by using the aggregated traffic information. Thus, the routing controller using the aggregated traffic information calculates the suitable routes without large link utilization by taking into consideration the upper bounds of the link utilization. This paper evaluates our method through simulations, where we demonstrated that the routing reconfiguration of each layer calculated suitable routes with short calculation times. Then, we reduced the link utilization immediately after traffic had changed by combining the routing reconfiguration of each layer.
