Network virtualization is one of the promising technologies that can increase flexibility, diversity, and manageability of networks. Building optimal virtual networks across multiple domains is getting much attention, but existing studies were based on an unrealistic assumption, that is, providers' private information can be disclosed; as is well known, providers never actually do that. In this paper, we propose a new method that solves this multi-domain problem without revealing providers' private information. Our method uses an advanced secure computation technique called multi-party computation (MPC). Although MPC enables existing unsecured methods to optimize virtual networks securely, it requires very large time to finish the optimization due to the MPC's complex distributed protocols. Our method, in contrast, is designed to involve only a small number of MPC operations to find the optimal solution, and it allows providers to execute a large part of the optimization process independently without heavy distributed protocols. Evaluation results show that our method is faster than an existing method enhanced with MPC by several orders of magnitude. We also unveil that our method has the same level of embedding cost.

In DHT network, a node can get/put a requested data by only log N look-up steps. However, conventional DHT network only supports single query look-up to search data. From the reason, each node in a DHT network must execute look-up process for each query even if a large number of put and get operations are executed. Therefore, this results in high network load in massive data management such as MapReduce, sensor network, and web information. To address the problem, we propose multiple queries look-up architecture using range information feedback (MARIF). MARIF extends the conventional KBR protocol to supports range information that is a scope of ID space a node keeps. When a source node receives range information from a destination node, the source node checks all queries in the range information and forwards queries matching the range information to the destination node directly. This effectively reduces the number of look-up queries and the network load for the IP network. In addition, MARIF can be implemented into conventional DHT networks and can easily be combined to effective DHT routing algorithms such as Chord, Kademlia, Pastry, and one-hop DHT. In evaluation, we implement MARIF into three DHT networks and compare its performance with that of conventional query bundling mechanisms based on the KBR protocol. The results show that MARIF reduces by up to 40% the total number of forwarding queries to put data compared with other mechanisms. In addition, MARIF saves the number of forwarding queries per look-up process by up to 85% compared to other mechanisms with low bundling overhead.

Virtual network embedding has been intensively studied for a decade. The time complexity of most conventional methods has been reduced to the cube of the number of links. Since customers are likely to request a dense virtual network that connects every node pair directly (|E|=O(|V|2)) based on a traffic matrix, the time complexity is actually O(|E|3=|V|6). If we were allowed to reduce this dense network to a sparse one before embedding, the time complexity could be decreased to O(|V|3); the time saving would be of the order of a million times for |V|=100. The network reduction, however, combines several virtual links into a broader link, which makes the embedding cost (solution quality) much worse. This paper analytically and empirically investigates the trade-off between the embedding time and cost for the virtual network reduction. We define two simple reduction operations and analyze them with several interesting theorems. The analysis indicates that an exponential drop in embedding time can be achieved with a linear increase in embedding cost. A rigorous numerical evaluation justifies the desirability of the trade-off.

Traffic matrix (TM) estimation has been extensively studied for decades. Although conventional estimation techniques assume that traffic volumes are unchanged between origins and destinations, packets are often lost on a path due to traffic burstiness, silent failures, etc. Counting every path at every link, we could easily get the traffic volumes with their change, but this approach significantly increases the measurement cost since counters are usually implemented using expensive memory structures like a SRAM. This paper proposes a mathematical model to estimate TMs including volume changes. The method is established on a Boolean fault localization technique; the technique requires fewer counters as it simply determines whether each link is lossy. This paper extends the Boolean technique so as to deal with traffic volumes with error bounds that requires only a few counters. In our method, the estimation errors can be controlled through parameter settings, while the minimum-cost counter placement is determined with submodular optimization. Numerical experiments are conducted with real network datasets to evaluate our method.

The routing efficiency of structured overlay networks depends on the consistency of pointers between nodes, where a pointer maps a node identifier to the corresponding address. This consistency can, however, break temporarily when some overlay nodes fail, since it takes time to repair the broken pointers in a distributed manner. Conventional solutions utilize “backpointers” to quickly discover any failure among the pointing nodes, which allow them to fix the pointers in a short time. Overlay nodes are, however, required to maintain backpointers for every pointing node, which incurs significant memory and consistency check overhead. This paper proposes a novel light-weight protocol; an overlay node gives a “living will” containing its acquaintances (backpointers) only to its successor, thus other nodes are freed from the need to maintain it. Our carefully-designed protocol guarantees that all acquaintances are registered via the living will, even in the presence of churn, and the successor notifies the acquaintances for the deceased. Even if the successor passes away and the living will is lost, the successor to the successor can identify the acquaintances with a high success ratio. Simulations show that our protocol greatly reduces memory overhead as well as the detection time for node failure with the cost being a slight increase in messaging load.