Mobile robot swarms using multiple moving robots cooperatively have attracted increasing attention in various problems, such as searching a target location or planning a path to a target. In this study, two types of multi-hop network establishment algorithms with point-to-multipoint connections using a mobile robot swarm are proposed. In these algorithms, a robot swarm autonomously establishes a multi-hop network with branching points between multiple targets where events occur simultaneously and an operator at a remote base station (BS). The point-to-multipoint network is generated using particle swarm optimization with the unique enhanced moving target technique, in which a robot that stops at an adequate position incrementally updates the next stopping position of the robot swarm while exploring adequate branching points. Simulations demonstrate that the proposed algorithms can achieve a higher ratio of successful network generation and smaller numbers of robots and movement steps for network generation compared with those of the existing point-to-point network establishment algorithm.

A mobile robot swarm using multiple robots cooperatively has attracted increasing attention in various application domains due to its advantageous features compared to a single robot, such as expanding the range of applications, relaxing the performance requirements for individual robots, and improving robustness. In this study, a mobile robot swarm algorithm based on particle swarm optimization is proposed, where the unique moving target technique is introduced to efficiently establish an autonomous multi-hop network between a target position where an event occurs and an operator at a remote base station, e.g., for monitoring real-time information and taking initial actions in a dangerous area with unstable communication environment. In the moving target technique, the oldest robot stopping at a suitable position updates the next target position of a mobile robot swarm step by step. In this manner, a multi-hop network is established between the original target and an operator at a base station by exchanging local information between neighboring robots while avoiding collisions with obstacles. We demonstrated that a mobile robot swarm using the proposed algorithm can establish an efficient multi-hop network with a higher success rate than the existing algorithm. Moreover, it can establish a flexible multi-hop network that adjusts to a placement pattern of obstacles without collisions.

Network bandwidth reservation is a representative service that utilizes the advantages of software-defined networks, such as flexibility, in which users directly reserve network resources on an on-demand basis. An instantaneous response to user requests (e.g., less than 1 s) and a high request acceptance ratio (e.g., over 90%) are required to provide bandwidth reservation services extensively. In this study, we propose a bandwidth reservation method to meet these two requirements by combining machine learning (ML) and linear programming (LP) technologies, particularly for unpredictable bandwidth demands that occur when an arbitrary user requires an infrequent or unexpected network bandwidth, in which the usage time is strictly indicated. In the proposed method, a user request is instantaneously and intuitively judged as accepted or rejected using ML, following which the network resource for accepted requests is optimally allocated using LP. We demonstrate that the proposed method, which adopts a basic multi-layered neural network, can achieve a high request acceptance ratio and adequate network resource allocation within a 10% difference compared to the ideal solution. In addition, the request judgment time of the proposed method is sufficiently short, at less than 1 ms, to achieve an instantaneous response.

Changing amount of radiation dose has been a great concern by citizen near the difficult-to-return area after the Fukushima Daiichi nuclear disaster. Rigorous assessment of public safety including inaccessible forest areas at a meter level is one of the keys in the disaster recovery plan. Each measurement point near the ground surface in UAV (Unmanned Aerial Vehicle) sensing are exposed from the effects of radiation emission from various angles in the fields including forest and plain, and thus acquisition of the attenuation characteristics on site is not realistic by simply using the spatial integration of point-kernels. The proposed method in this paper utilizes a double exponential curve for the least-squares fitting. The field test at a resident in the forests near the difficult-to-return area was performed, and we found not only a strong correlation between measured value and estimation result of the proposed method (r = 0.86, p < 0.01) but also the improvement of more than 10% in RMSE (root mean squared error) from results of the existing methods using an exponential decay function. Importantly, the experimental result suggested that the proposed method completely accepts to use the different measurement data, both measurement points near the ground surface and the flight heights during the UAV sensing.

Network bandwidth reservation is a representative service, where users directly reserve network resources on an on-demand basis. It utilizes the advantages of software defined networks, such as flexibility. To provide bandwidth reservation services extensively, an instantaneous response to user requests (e.g., less than 1 s) and a high user request acceptance ratio (e.g., over 90%) are required. In this study, we propose a bandwidth reservation method to meet these two requirements by combining machine learning (ML) and linear programming (LP), particularly for unpredictable bandwidth demands in which the usage time is strictly indicated. In the proposed method, a user request is instantaneously judged through ML, and network resource allocation, including traffic routing, is optimally determined through LP. We demonstrate that the proposed method provides a suboptimal acceptance ratio with a difference of less than 1% compared with the optimal solution and an instantaneous response of less than 0.1 ms under a general computation environment.

We proposes a backbone network resource optimization algorithm for video communications that use edge computing. In the current video communication architecture, the key component of video communication, called the multi-point control unit (MCU), is deployed in the central cloud server, and its bandwidth consumption in the backbone network becomes enormous as the video resolution and the frequency of use increase. By implementing edge computing, the MCU can be deployed at the entrance node of the backbone network. This allows (i) a local loopback of video traffic at an edge, and (ii) traffic compression (e.g., thumbnailing) between edge nodes. Though these characteristics can reduce the resource consumption of the backbone network, the edge deployment and routing (EDR) problem, classified as NP-hard, should be solved to sufficiently reduce the bandwidth. To solve the NP-hard EDR problem within a feasible period, we propose a divide and merge algorithm based on the linear programming approach. With our algorithm, bandwidth consumption using edge computing is reduced by approximately 30% compared with the current video communication architecture in the world-wide network.

A topology control method for mobile ad hoc networks is proposed, in which the optimal topology of each topology update interval is determined by considering both the dynamic positions of one-hop neighboring nodes and the minimization of cumulative energy consumption to send data during the update interval. This approach of adopting the topology optimized over the update interval differs from the existing approach in which the topology update frequency is increased by shortening the update interval. Simulation results demonstrate that the proposed method reduces the energy consumed in sending data under various evaluation conditions compared to a benchmark method in which the topology is determined using the initial positions of one-hop neighboring nodes at update time. Additionally, the proposed method is practical because it takes only several tens of milliseconds to determine the optimal topology of the update interval, even when using a general CPU employed in embedded devices. Further, the applicability conditions of the proposed method are revealed and compared to an existing method that increases the topology update frequency by shortening the update interval.

Physical network resource deployment to meet future traffic growth is a significant issue for network operators because it has a significant impact on the overall performance of next-generation networks. In this paper, we propose an effective design method of physical network resource deployment by considering an adequate trade-off between the number of additional physical network resources, Q, and operation risk in both the pipe and the hose traffic models. Operation risk, which includes complex network design and misconfiguration of network components, is a significant issue in practical network operation because it increases the capital expenditure and operating expenses, in addition to preventing the provision of stable commercial services. We focus on reducing the number of links with additional capacity, Nu, as the first step to reduce operation risk. Numerical evaluations are performed to compare our method with a benchmark method that minimizes the number of physical network resources. Thus, our method is shown to be able to provide Pareto-optimal solutions that can reduce Nu significantly with a slight increase in Q. For example, Nu is reduced by 50% and 40% while increasing Q by 20% and only 2% in the pipe model and the hose model, respectively.

When an unexpected large-scale communication network disruption occurs, the damaged network will be recovered gradually and the recovery process involves multiple recovery stages. The present paper proposes a network recovery method that can determine an appropriate recovery order of damaged network components over multiple recovery stages considering both prompt network service recovery and fair traffic recovery to meet traffic demand. In particular, network service recovery is assigned a higher priority. The optimal recovery order problem is formulated by mixed integer linear programming (MILP), and the problem-decomposition method is also introduced for application in instances when it is difficult to solve the problem of large-scale failures within a practical computation time. The effectiveness of the proposed method was numerically evaluated. The results indicate that we can determine a more appropriate recovery order in terms of both network service recovery and traffic recovery as compared with a benchmark method, and that the computation time is drastically reduced by using the problem-decomposition method.

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.

This paper proposes an Internet protocol (IP) state migration method for developing resource-portable IP routers that are not virtual-machine based but commercial based. Resource-portable IP routers have the potential for achieving a sustainable network by functioning as a shared backup router. While previous studies relied on a virtualized technology (e.g., a virtual machine-based router on commodity hardware), current commercial routers was not virtualized but implemented as a proprietary hardware and software. We achieved IP state migration for a proprietary router with control packet sniffing of the open shortest path first (OSPF) protocol and border gateway protocol (BGP) peer masquerade using a software-defined network controller. We implemented our method and verified the accuracy of the state migration of routing tables generated using OSPF and BGP.

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.

A high-speed and distributed ATM switch architecture, called the TORUS switch, is proposed with the aim of achieving a terabit-per-second ATM switching system. The switch is a distributed and scalable internal speed-up crossbar-type ATM switch with cylindrical structure. The self-bit-synchronization technique and optical interconnection technology are combined to achieve gigabit-rate cell transmission, where high-density implementation technologies such as multichip module technology are not required at all. Also, distributed contention control based on the fixed output-precedence scheme is newly adopted. This control is very suitable for high-speed devices because its circuit is achieved with only one gate in each crosspoint. A TORUS switch is fabricated as a 4/spl times/2 switch module using optical interconnection technology and very high-speed crosspoint LSIs, constructed using an advanced Si-bipolar process. Measured results confirm that the TORUS switch can be used to realize an expandable terabit-rate ATM switch.