The availability of IP networks has increased its importance due to the evolving use of real-time and mission-critical applications on IP networks. Methods for preparing alternate routing tables that can be used for fast restoration from link failures have been investigated. In such methods, each node has to compute a number of alternate routing tables in advance since they have to prepare for each potential failure. The resulting huge number of alternate routing tables has prevented these methods from being deployed. In this paper, we propose a method for reducing the number of alternate routing tables for link failure. It analyzes three types of shortest path trees on the basis of link-state information. We show that the number of alternate routing tables can be reduced to 1/100, on average, from that with the conventional method, and that they are small enough to be stored in the memory of IP routers.

Topology information has become more important for management of LANs due to the increasing number of hosts attached to a LAN. We describe three Ethernet topology discovery techniques that can be used even in LANs with Ethernet switches that have no management functionality. Our "Shared Switch Detection (SSD)" technique detects the Ethernet tree topology by testing whether two paths in the network share a switch. SSD uses only general MAC address learning. By borrowing MAC addresses from hosts, SSD can be run from a single host. The second technique determines whether two paths between two pairs of hosts contain a switch. The third reduces the number of shared switch detections. Simulation showed that these techniques can be used to detect the Ethernet topology with a reasonable search cost. Examination on a real-world testbed showed that they could detect an Ethernet topology consisting of six hosts and two switches within one second.

The primary challenges faced by wireless sensor networks are how to construct the shortest spanning tree and how to determine the optimal sink node position in terms of minimizing the data transmission times and their variances for data gathering from all sensor nodes to a sink node. To solve these two problems, we propose a novel algorithm that uses the polygonal affine shortening algorithm with flow aggregation. This algorithm enables a wireless sensor network that has movable sensor nodes and one movable sink node to self-organize the shortest spanning tree and self-determine the optimal sink node position in a fully distributed manner. We also show that our algorithm is faster than the existing shortest path algorithm in terms of computational complexity.

Software-defined networking (SDN) technology enables us to flexibly configure switches in a network. Previously, distributed SDN control methods have been discussed to improve their scalability and robustness. Distributed placement of controllers and backing up each other enhance robustness. However, these techniques do not include an emergency measure against large-scale failures such as network separation induced by disasters. In this study, we first propose a network partitioning method to create a robust control plane (C-Plane) against large-scale failures. In our approach, networks are partitioned into multiple sub-networks based on robust topology coefficient (RTC). RTC denotes the probability that nodes in a sub-network isolate from controllers when a large-scale failure occurs. By placing a local controller onto each sub-network, 6%-10% of larger controller-switch connections will be retained after failure as compared to other approaches. Furthermore, we discuss reactive emergency reconstruction of a distributed SDN C-plane. Each node detects a disconnection to its controller. Then, C-plane will be reconstructed by isolated switches and managed by the other substitute controller. Meanwhile, our approach reconstructs C-plane when network connectivity recovers. The main and substitute controllers detect network restoration and merge their C-planes without conflict. Simulation results reveal that our proposed method recovers C-plane logical connectivity with a probability of approximately 90% when failure occurs in 100 node networks. Furthermore, we demonstrate that the convergence time of our reconstruction mechanism is proportional to the network size.

Network function virtualization (NFV) enables network operators to flexibly provide diverse virtualized functions for services such as Internet of things (IoT) and mobile applications. To meet multiple quality of service (QoS) requirements against time-varying network environments, infrastructure providers must dynamically adjust the amount of computational resources, such as CPU, assigned to virtual network functions (VNFs). To provide agile resource control and adaptiveness, predicting the virtual server load via machine learning technologies is an effective approach to the proactive control of network systems. In this paper, we propose an adjustment mechanism for regressors based on forgetting and dynamic ensemble executed in a shorter time than that of our previous work. The framework includes a reducing training data method based on sparse model regression. By making a short list of training data derived from the sparse regression model, the relearning time can be reduced to about 57% without degrading provisioning accuracy.

This article proposes a method to improve the performance of Message Exchange Network (MeNW) which is modern data distribution network incorporating the search and obtain mechanism. We explore an idea of shortcut creation which can be widely adapted to a topological structure of various network applications. We first define a metric called Efficiency Coefficient (EC) that quantifies the performance enhancement by a shortcut creation. In the design of EC, we consider not only diameter of the topology but also the amount of messages exchanged in the network. Then, we theoretically analyze the creation of a single optimal shortcut in the system based on the performance metric. The simulation results show that the shortcut by the proposed method reduces the network resource to further 30% compared with conventional approaches.

This article introduces a self-organizing model which builds the topology of a DHT mapping system for ICN. Due to its self-organizing operation and low average degree of maintenance, the management overhead of the system is reduced dramatically, which yields inherent scalability. The proposed model can improve latency by around 10% compared to an existing approach which has a near optimal average distance when the number of nodes and degree are given. In particular, its operation is simple which eases maintenance concerns. Moreover, we analyze the model theoretically to provide a deeper understanding of the proposal.

How to retrieve the closest content from an in-network cache is one of the most important issues in Information-Centric Networking (ICN). This paper proposes a novel content discovery scheme called Local Tree Hunting (LTH). By adding branch-cast functionality to a local tree for content requests to a Content-Centric Network (CCN) response node, the discovery area for caching nodes expands. Since the location of such a branch-casting node moves closer to the request node when the content is more widely cached, the discovery range, i.e. the branch size of the local tree, becomes smaller. Thus, the discovery area is autonomously adjusted depending on the content dissemination. With this feature, LTH is able to find the “almost true closest” caching node without checking all the caching nodes in the in-network cache. The performance analysis employed in Zipf's law content distribution model and which uses the Least Recently Used eviction rule shows the superiority of LTH with respect to identifying the almost exact closest cache.

Most wireless networks consist of heterogeneous nodes with diverse characteristics. These heterogeneous nodes have various moving characteristics such as speed and pausing time. Since conventional wireless routing schemes are designed for networks with homogeneous mobility, it is difficult to accomplish communication without degrading its quality, e.g., packet reachability and delay, in networks with heterogeneous mobility. In this paper, we propose efficient extensions of a proactive routing protocol to achieve sufficient communication quality in networks with heterogeneous mobility. The proposed extensions consist of three features, i.e., differential topology update, unidirectional movement notification and link quality based route calculation. Complementary actions among these functions can improve communication quality with acceptable control overhead. Simulation results reveal that the proposed scheme can achieve higher packet reachability and lower delay with low control overhead compared with existing routing schemes.

Information-Centric Networking (ICN) originally innovated for efficient data distribution, is currently discussed to be applied to edge computing environment. In this paper, we focus on a more flexible context, in-network computing, which is enabled by ICN architecture. In ICN-based in-network computing, a function chaining (routing) method for chaining multiple functions located at different routers widely distributed in the network is required. Our proposal is a twofold approach, On-demand Routing for Responsive Route (OR3) and Route Records (RR). OR3 efficiently chains data and multiple functions compared with an existing routing method. RR reactively stores routing information to reduce communication/computing overhead. In this paper, we conducted a mathematical analytics in order to verify the correctness of the proposed routing algorithm. Moreover, we investigate applicabilities of OR3/RR to an edge computing context in the future Beyond 5G/6G era, in which rich computing resources are provided by mobile nodes thanks to the cutting-edge mobile device technologies. In the mobile environments, the optimum from viewpoint of “routing” is largely different from the stable wired environment. We address this challenging issue and newly propose protocol enhancements for OR3 by considering node mobility. Evaluation results reveal that mobility-enhanced OR3 can discover stable paths for function chaining to enable more reliable ICN-based in-network computing under the highly-dynamic network environment.

The effect of inconsistencies in forwarding tables on the reachability of IP packets is evaluated. To improve a router's availability, in the architecture of current routers, the control element is separated from the forwarding element. However, a router with the current architecture cannot handle a notification for which the topology of the network system changes when its control element has stopped. In such a case, the router cannot update its own forwarding table, and an inconsistency between the forwarding tables of the router and those of the other routers will occur. To investigate the influence of this inconsistency, we formalize the network system, and derive the conditions under which such an inconsistency leads to unreachable routes. After that, the number of routes that are unreachable is evaluated by simulations. These simulations show that routing loops occur more frequently under the condition that a failed node is close to the restarting node or fewer links exist in the network system.