Shohei Kamamura

<p>An optical transport network is composed of optical transport systems deployed in thousands of office-buildings. As a common infrastructure to accommodate diversified communication services with drastic traffic growth, it is necessary not only to continuously convey the growing traffic but also to achieve high end-to-end communication quality and availability and provide flexible controllability in cooperation with service layer networks. To achieve high-speed and large-capacity transport systems cost-effectively, system configuration, applied devices, and the manufacturing process have recently begun to change, and the cause of failure or performance degradation has become more complex and diversified. The drastic traffic growth and pattern change of service networks increase the frequency and scale of transport-capacity increase and transport-network reconfiguration in cooperation with service networks. Therefore, drastic traffic growth affects both optical-transport-system configuration and its operational cycles. In this paper, we give an overview of the operational problems emerging in current nationwide optical transport networks, and based on trends analysis for system configuration and network-control schemes, we propose a vision of the future nationwide optical-transport-network architecture expressed using five target features.</p>

<p>Physical-network-resource deployment to meet future traffic growth is a significant issue for network operators because it is related to the ground design of next generation networks. In this paper, we propose an effective heuristic decomposition method of physical-network-resource deployment considering the balance between the amount of additional network resources Q and operation-risk. We focus on decreasing the number of physical links with additional capacity Nu to reduce operation-risk. Numerical evaluations indicate that, with our method, pareto-optimal solutions between Q and Nu can be designed with a smaller Nu, more than 50% smaller, compared with a benchmark method that minimizes Q.</p>

<p>We propose relaxed computation for the non-bifurcation progressive disaster recovery problem. When massive failure occurs, failed components are gradually repaired since repair resources are limited. Though there are studies on disaster recovery problem to maximize the amount of recovered traffic considering this assumption, they are based on the maximum flow approach, where traffic bifurcation on an arbitrary node is allowed. This condition is not practical in an actual environment. We first formulate non-bifurcation progressive disaster recovery problem as 0-1 integer linear programming. Because the problem is NP-hard, we present a problem-decomposition method and obtain an improvement of 13% over the benchmark method.</p>

When a massive network disruption occurs, repair of the damaged network takes time, and the recovery process involves multi stages. We propose a fast and flow-controlled multi-stage network recovery method that can determine the pareto-optimal recovery order of failed physical components reflecting the balance requirement between maximizing the total amount of traffic on all logical paths, called total network flow, and providing adequate logical path flows. The pareto-optimal problem is formulated by mixed integer linear programming (MIP). A heuristic algorithm, called the grouped-stage recovery order (GSR), is also introduced to solve the problem when the problem formulated by MIP is computationally intractable in a large-scale failure. The effectiveness of the proposed method was numerically evaluated. The results show that the pareto-optimal recovery order can be determined from the balance between total network flow and adequate logical path flows, the allocated minimum bandwidth of the logical path can be drastically improved while maximizing total network flow, and the proposed method with GSR is applicable to large-scale failures because a nearly optimal recovery order with less than 10% error rate can be determined within practical computation time.

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. (C) 2014 Elsevier B.V. All rights reserved.

We propose a virtual network topology (VNT) control method that is adaptive to environmental changes in a network. It is based on attractor selection, which models the biological systems that behave adaptively against changes in their surrounding environments. The simulation results indicate that our VNT control method adaptively responds to changes in network environments caused by node failure and constructs operational VNTs in more than 95% of simulation trials when 20% of nodes in the physical network fail simultaneously. © 2013 IEICE.

We investigate what kind of information should be exchanged for controlling multiple VNTs. Simulation results show number of reconfigurations to find good VNTs is significantly reduced with slightly increased, but still marginal, amount of information.

This paper proposes an IP fast rerouting method which can be implemented in OpenFlow framework. While the current IP is robust, its reactive and global rerouting processes require the long recovery time against failure. On the other hand, IP fast rerouting provides a milliseconds-order recovery time by proactive and local restoration mechanism. Implementation of IP fast rerouting is not common in real systems, however; it requires the coordination of additional forwarding functions to a commercial hardware. We propose an IP fast rerouting mechanism using OpenFlow that separates control function from hardware implementation. Our mechanism does not require any extension of current forwarding hardware. On the contrary, increase of backup routes becomes main overhead of our proposal. We also embed the compression mechanism to our IP fast rerouting mechanism. We show the effectiveness of our IP fast rerouting in terms of the fast restoration and the backup routes compression effect through computer simulations.

IP fast rerouting has widely been studied for realizing millisecond-order recovery on pure IP networks. This paper proposes IP fast rerouting using backup topologies against concurrent double failures. The main issue in recovering from multiple failures is avoiding forwarding loops. To avoid forwarding loops, we propose a deterministic forwarding algorithm, which estimates the concurrently occurring failures from the packet header information. We also propose an efficient backup topology design algorithm which is both loop-free and which reduces the number of backup topologies. Our key idea is preparing the adequate diversity of backup routes for arbitrary source and destination pairs by combination of backup topologies. For efficient computation of diverse routes, we propose a similarity comparison-based algorithm between the original topology and the backup topologies. Our algorithm can achieve nearly optimal loop-free restoration from double failures on realistic topologies without explicit failure notification.