Nagao Ogino

Virtual network embedding with multiple priority classes sharing substrate resources

Network virtualization is a promising approach for virtual network operators to configure their own inter-cloud networks flexibly on an inter-cloud substrate network. Virtual network operators specify multiple priority classes in order to satisfy different latency requirements for their inter-cloud network services with a variety of delay-sensitivities on their virtual networks. Furthermore, they may require substrate resource sharing among multiple priority classes in order to reduce the amount of substrate resources assigned to them. Meanwhile, it is desirable for a substrate network provider that multiple virtual networks can share substrate resources since the total amount of substrate resources required can be reduced due to the effect of statistical multiplexing. This paper formulates a novel virtual network embedding problem and proposes a heuristic virtual network embedding method to minimize the total substrate resources required when the virtual network operators request substrate resource sharing among multiple priority classes within their virtual networks. Based on the proposed method, multiple virtual networks can maximally share substrate resources with one another while sharing substrate resources on an equal basis. The effect of substrate resource sharing among multiple priority classes and multiple virtual networks is quantitatively assessed through extensive simulations, and advantageous topologies for requested virtual networks and substrate networks are also presented.

Heuristic Computation Method for All-Optical Monitoring Trails Terminated at Specified Nodes

Detecting degraded optical signal quality solely at the terminal nodes of monitoring trails is a promising approach for reducing the fault management cost in all-optical mesh networks. However, this approach requires that monitoring trails are routed so that all failures can be localized using route information for the monitoring trails where degraded signal quality is detected. Thus, this paper proposes a novel heuristic method to compute the least number of monitoring trails required to localize all link failures in an arbitrary failure scenario. In particular, the proposed method can compute the monitoring trails terminating only at specified nodes to which monitors can be attached. This paper verifies the effectiveness of the proposed method by comparison with the optimum method based on an integer programming model and an existing heuristic method. Using the proposed method, an accurate estimate of the least number of monitoring trails and their routes can be computed quickly, even for practical large-scale networks.

Lightweight Boolean Network Tomography Based on Partition of Managed Networks

Boolean network tomography is a promising technique to achieve fault management in networks where the existing IP-based troubleshooting mechanism cannot be used. Aiming to apply Boolean network tomography to fault management, a variety of heuristic methods for configuring monitoring trails and paths have been proposed to localize link failures in managed networks. However, these existing heuristic methods must be executed in a centralized server that administers the entire managed network and the methods present scalability problems when applied to large-scale managed networks. Thus, this paper proposes a novel scheme for achieving lightweight Boolean network tomography in a decentralized manner. The proposed scheme partitions the managed network into multiple management areas and localizes link failures independently within each area. This paper also proposes a heuristic network partition method with the aim of efficiently implementing the proposed scheme. The effectiveness of the proposed scheme is verified using typical fault management scenarios where all single-link failures and all dual-link failures are localized by the least number of monitoring paths on predetermined routes. Simulation results show that the proposed scheme can greatly reduce the computational load on the fault management server when Boolean network tomography is deployed in large-scale managed networks. Furthermore, the degradation of optimality in the proposed scheme can be mitigated in comparison with a centralized scheme that utilizes heuristics to reduce the computational load on the centralized server.

Decentralized boolean network tomography based on network partitioning

Network tomography is a promising technique to achieve fault management in networks where the existing IP-based troubleshooting mechanism cannot be used. Aiming to apply Boolean network tomography to fault management, various heuristic methods for configuring monitoring trails have been proposed to localize link failures in all-optical mesh networks. However, these existing heuristic methods must be executed in a centralized server that administers the entire managed network, and present scalability problems when they are applied to large-scale managed networks. Thus, this paper proposes a novel scheme for achieving lightweight Boolean network tomography in a decentralized manner. The proposed scheme partitions the managed network into multiple management areas and localizes link failures independently within each area. This paper also proposes a heuristic network partition method with the aim of implementing the proposed scheme efficiently. The effectiveness of the proposed scheme is verified using a typical fault management scenario, where all the single-link failures are localized by the monitoring paths the routes of which are predetermined. Simulation results show that the proposed scheme can greatly reduce the computational load on the fault management server when Boolean network tomography is deployed in large-scale managed networks.

Multicast delivery scheme for threshold secret shared content

A threshold secret sharing scheme can deliver important content reliably using redundant delivery routes via a network. Furthermore, simultaneous delivery of the threshold secret shared content to multiple receivers can achieve efficient resource utilization thanks to multicast and network coding techniques. Nevertheless, the network coding technique results in a tradeoff between reliability and efficiency. This paper proposes a multicast delivery scheme for threshold secret shared content that can control the tradeoff between reliability and efficiency. In the proposed scheme, all the pieces obtained from the original content are grouped in advance, and network coding is only applied to the pieces included in the same group. This paper also proposes two kinds of heuristic multicast delivery route computation methods to optimize the proposed multicast delivery scheme in networks on a practical scale. The evaluation results show that the proposed scheme adopting an optimized number of groups can actually minimize the total link bandwidth required while satisfying the given requirement on content loss probability.

Reliable delivery route computation for threshold secret shared content

A threshold secret sharing scheme can protect content by dividing it into many pieces and distributing them over different servers. This scheme can also be utilized for reliable delivery of the content. Thanks to this scheme, the receiver can still reconstruct the original content even if several pieces are lost on their delivery routes due to the occurrence of a multiple-link failure. This paper aims to obtain reliable delivery routes for the pieces, as this will minimize the probability that the receiver cannot reconstruct the original content. Although such a route optimization problem can be formulated using an ILP (Integer Linear Programming) model, optimum route computation based on the ILP model requires large amounts of computational resources. Thus, this paper proposes a lightweight method for computing suboptimum delivery routes. The proposed greedy method computes each of the delivery routes successively by using the conventional shortest route algorithm repeatedly. The distance of the links is adjusted iteratively on the basis of the given probability of failure on each link and utilized for the calculation of each shortest route. The results of a performance evaluation show that the proposed method based on the strict adjustment of the link distance can compute sufficiently optimum delivery routes at less than 100 seconds, even in backbone networks of a practical scale.

An evolvable network design approach with topological diversity

As environments surrounding the Internet become more changeable, a design approach that requires less equipment to scale up networks against the traffic growth arising from various environmental changes is needed. Here, we propose an evolvable network design approach where network equipment is deployed without a predetermined purpose. We enhance topological diversity in the network design by minimizing the mutual information. Evaluations show that, compared to networks built with ad-hoc design method, networks constructed by our design approach can efficiently use network equipment in various environments. Moreover, we show that, even considering the physical lengths of links, the approach of increasing topological diversity can lead to an evolvable network.

Designing an evolvable network with topological diversity

As environments surrounding the Internet become more changeable, a design approach is needed that requires less equipment to scale up networks against traffic growth resulting from various environmental changes. Here, we propose an evolvable network design approach in which network equipment is deployed without predetermined purpose rather than for a preplanned purpose. We use mutual information on node degree to measure the topological diversity of networks, and maximize topological diversity in the network design by minimizing the mutual information. Evaluations show that, compared to networks based on an ad hoc design method, networks constructed by our design approach can re-use already installed equipment in different environments.

A heuristic computation method for monitoring trails terminated at specified nodes

Detecting degraded signal quality solely at the terminal points of monitoring trails is a promising approach for reducing the fault management cost in networks. However, this approach requires that monitoring trails are routed so that all failures can be localized by using route information for the monitoring trails where degraded signal quality is detected. Thus, this paper proposes a novel heuristic method to compute the least number of monitoring trails required to localize all link failures in an arbitrary failure scenario. The proposed method can compute the monitoring trails terminating at the particular nodes to which monitors can be connected. This paper verifies the effectiveness of the proposed method by comparison with the global optimization method and an existing heuristic method. Using the proposed method, an accurate estimate of the least number of monitoring trails and their routes can be computed quickly, even for practical large-scale networks.