Shohei Kamamura

Minimum Backup Configuration-Creation Method for IP Fast Reroute

IP Fast Reroute techniques have been proposed for achieving fast failure recovery in just a few milliseconds. The basic idea of IP Fast Reroute is to reduce recovery time after failure by precomputing backup routes. A multiple routing configurations (MRC) algorithm has been proposed for obtaining IP Fast Reroute. MRC prepares backup configurations, which are used for finding a detour route after failure. On the other hand, requiring too many backup configurations consumes more network resources. It is necessary to recover more traffic flows with fewer backup configurations to ensure scalability. We propose a new backup configuration-creation algorithm for maximizing traffic flows which are fast recovered as much as possible under a limited number of backup configurations. The basic idea is to construct a spanning tree excluding failure links with higher link-loads in each backup configuration. We show that our algorithm has more robust on actual large IP networks.

Optimization of light-path configuration order in IP over WDM networks using fast traffic matrix estimation

We propose an algorithm for determining light-path configuration order to minimize the reconfiguration time from a disrupted state to a suboptimal state. It computes a near-optimal solution within one minute on a 1000-node network.

Dispersing Hotspot Traffic in Backup Topology for IP Fast Reroute

A backup topology design algorithm for avoiding congestion in IP fast reroute is presented. In IP fast reroute techniques, detour routes are computed by using backup topologies. Reducing the number of backup topologies is the main problem, but some links will become overloaded if the number of backup topologies is reduced. The proposed backup topology design algorithm splits the traffic on high load links to other links by considering network conditions, such as the traffic matrix or topology. The key idea of the algorithm is a new concept called the special node, which has a higher node degree in a backup topology, to handle the backup topology design problem. The effectiveness of the algorithm in terms of maximum link load reduction is quantitatively shown.

Scalable backup configurations creation for IP fast reroute

IP Fast Reroute techniques have been proposed to achieve fast failure recovery in just a few milliseconds. The basic idea of IP Fast Reroute is to reduce recovery time after failure by precomputing backup routes. A multiple routing configurations (MRC) algorithm has been proposed for obtaining IP Fast Reroute. MRC prepares backup configurations, which are used for finding a detour route after failures. However, this current algorithm requires too many backup configurations to recover from failures. We propose a new backup configuration computation algorithm for reducing configurations as much as possible. The basic idea is to construct a spanning tree excluding failure links in each backup configuration. We show that the effectiveness of our algorithm is especially high in large-scale power-law networks.

Multi-staged network restoration from massive failures considering transition risks

In a scenario of restoration from massive failures, a network is repaired through multiple restoration stages because availability of repair resources is limited. In a practical case, a network operator should assure the reachability of important traffic in transient stages, even as risks and/or operational overheads caused by stage transitions are suppressed. We discuss the novel problem of optimizing both traffic recovery ratio and transition risks caused by paths switching operation. We formulate our problem as linear programming, and show that it obtains Pareto-optimal solutions of traffic recovery versus transition risks. We also propose a heuristic algorithm for applying networks consisting of a few hundred nodes, and it could produce sub-optimal solutions within 4% difference from optimal solutions.

Policy-based resource management in virtual network environment

Network virtualization offers users flexibility and controllability in their network. Virtual network users directly customize their own network topologies for a specific purpose by leasing physical resources from physical network providers. However, the autonomic topology managed independently by each user can lead to the instability or performance degradation. We present a framework for policy-based resource management applied to the virtual network environment. Our framework enables sufficient flexibility and controllability for each user; at the same time, the physical network operator can regulate excessive resource usage by the users. We introduce a two-phase resource management model that adds a policy-based resource management function to the existing GMPLS architecture. In addition, we present a formulation of the optimal virtual network design problems reflected by two different requirements of users. We also developed network operation tools to demonstrate our framework.

IP fast reroute control using centralized control plane architecture

An IP fast reroute control architecture using a centralized control plane where the control plane and data plane are physically separated is presented. In IP fast reroute processes, route computation and failure restoration are independently performed. Our architecture places the route computation function in the central control server to ensure scalability. As for route configuration, the size of the backup routing table is a significant issue in IP fast reroute architecture. We present a backup-table sharing method to reduce its size.

Multi-stage network recovery considering traffic demand after a large-scale failure

When a massive network disruption occurs, repair of the damaged network takes time, and the recovery process involves multiple stages. We previously proposed a multi-stage network recovery method for determining 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 to meet traffic demand. The pareto-optimal problem is formulated by mixed integer linear programming (MILP). In this paper, we propose a heuristic algorithm, called grouped-stage recovery (GSR), to solve the problem which cannot be solved with our previous method in a large-scale failure within a practical time. We numerically evaluated the effectiveness of our method with GSR. The results show that our method with GSR is applicable to large-scale failures because a nearly optimal recovery with less than 10% difference rate can be determined within practical computation time.

Dynamic resource allocation mechanism for managed self-organization

Future network should flexibly deal with unexpected network changes caused by the diversification of the network services. In this paper, we propose a managed self-organizing network concept and a dynamic resource allocation mechanism, called as DRAMS. In the managed self-organizing network, multiple virtual networks are accommodated on a single physical network and controlled autonomically based on self-organization. Due to the sharing of limited physical resources, resource contention among virtual networks will be inevitably caused. To cope with this issue, we introduce a dynamic resource allocation to regulate the resource usage of ill-behaved virtual networks. Our research goal is to establish a management mechanism for controllable self-organizing networks. The proposed mechanism allows self-organizing control by virtual networks and just indirectly controls the behavior of virtual network in order to avoid resource contention and improve resource efficiency.

Resolution of network topology using fast graph mining

We propose algorithms that uses fast graph mining for resolving the network topology to a locally regulated area defined as a component of network topology. Though the IP backbone network should be reconfigured periodically in accordance with environmental changes, reconfiguration results in heavy workload, such as routing re-designs or testing these re-designs for network operators. If a network can be reconfigured within the component, however, we can drastically reduce the operation workload for network reconfiguration. For finding the components from the network topology, we should solve the subgraph isomorphism problem, which is NP-hard. We propose the heuristic graph mining algorithm that reduces the size of search space by considering network operating conditions. We visualize the results of components analysis, and show that the computation finishes within the practical time.