To achieve carbon neutrality in telecommunication networks, this paper focuses on a virtual network (VN) allocation problem for telecommunication networks powered by renewable energy (RE). One of the most critical issues is the fluctuation of RE power caused by uncertain weather conditions. Under the fluctuation of RE power, we must allocate multiple VNs so that RE power is efficiently used while avoiding waste. To deal with the fluctuation problem of RE power, we model RE power as a stochastic variable that follows a certain probability distribution. However, there are still challenges in accurately estimating the true distribution due to the limited size and nonstationarity of RE power data. To this end, we propose a distributionally robust VN allocation model that minimizes the expectational cost of the total excess power for the worst-case probability distribution in the set of all possible distributions that generate actual RE power, i.e., the uncertainty set. The uncertainty set is defined on the basis of the Wasserstein ball, in which the center is an empirical distribution constructed from the accumulated RE data and the radius is a certain Wasserstein metric. Then, the true probability distribution is assumed to be in the uncertainty set. Finally, through numerical experiments, the effectiveness of the proposed method is shown even if the estimation of RE power distribution is uncertain due to the small size of RE power data.

To achieve carbon neutrality in telecommunications networks, the introduction of renewable energy is expected to further advance in the future. However, renewable energy such as solar power generation can experience large fluctuations in power output depending on weather conditions. Therefore, depending on the location and time period, there may be places where renewable energy cannot be fully consumed and surplus power is generated, and there may be places where renewable energy is not sufficient to meet the power demand. Toward network carbon neutrality, new methods need to be established from a network perspective that avoid inefficient power management problems caused by fluctuations in renewable energy. To solve this problem, we have been studying the control of power consumption locations and time periods by allocating workloads using virtualization technology. In this paper, we propose a workload scheduling method to increase renewable energy use. The problem to maximize the renewable energy use is formulated, and to solve it in a short time, a heuristic search method is proposed. The simulation results show that the proposed control method can increase the amount of renewable energy use while having tradeoffs with communication quality and equipment efficiency.

This paper analyzes numerically the minimum turning radius of a quad-plane UAV in high-speed flights based on its dynamic model. The smallest turning radius that satisfies the flight conditions for a steady level turn is searched for by numerical optimization at various flight speeds. The turning radius is significantly reduced by utilizing the four rotors mounted on the UAV for rotary-wing mode, although they are not used in the conventional fixed-wing mode of flight. The four rotors allow the UAV to increase its lift and to control its moment in addition to the aerodynamic lift and moment. This enhanced maneuverability of the UAV due to the rotors leads to higher turning performance. The numerical results also show that the reduction in turning radius depends on the flight speed.

This paper reveals that the turning radius of a tiltrotor UAV during high-speed flights can be significantly reduced by utilizing the redundancy in control inputs. Based on a dynamic model of the UAV, the flight conditions of steady level turns are analyzed to numerically search for the minimum turning radius when all the actuators installed in the UAV are utilized. Numerical results indicate that adding lift with sub-rotors installed for rotary-wing mode makes it possible to increase the roll angle during level turns while reducing the turning radius. The tilt angle of main rotor can also be chosen within a certain range to reduce the turning radius. The feasibility of such steep turns is checked by numerical simulations using a feedback control.

In this paper, we consider a physical network powered by renewable energy resources and a virtual network (VN) of a client service, which is composed of a client node, a virtual machine (VM) node, and a virtual link. Then, a robust VN allocation problem is formulated for multiple client services: given the location of client nodes, find the allocation of VM nodes and virtual links to maintain robustness for the uncertainty of traffic demands and renewable energy power; i.e., their prediction error. Specifically, we propose two robust allocation models: robust VN allocation model and two-stage robust VN allocation model, which are formulated on the basis of robust optimization and two-stage robust optimization, respectively. To show the effectiveness of two robust proposed models, we conduct numerical experiments under various prediction error patterns of traffic demands and renewable energy power. When prediction errors are large, the two proposed models acquire better average and worst-case performance than a deterministic model that does not handle prediction errors. In addition, we observe some patterns where the two-stage robust VN allocation model acquires better average performance than the robust VN allocation model instead of deteriorating the worst-case performance.

The purpose of the paper is to analyse the possible parameters of extratropical cyclones (ETCs) as they would occur in the Baltic Sea area at the end of the 21st century and in the past during the Holocene thermal maximum. Using a modelling system composed of the Weather Research and Forecasting (ARW-WRF) atmospheric model, Finite Volume Community Ocean Model (FVCOM), and surrogate background conditions, the results showed that changes in cyclone parameters are more profound under steeper climate change scenarios (RCP8.5) and under higher air temperatures. Most likely, the North Atlantic ETCs will become slightly stronger, but also the uncertainty increases. Nonlinear interactions between ice melt, North Atlantic current systems and atmospheric parameters probably induce an uncertainty both into future and past storminess reconstructions.

In this study, we investigated morphological changes including the formation of beach scarp behind the breakwaters based on field surveys and numerical simulations at Aoyama beach in Niigata coasts, Japan. The morphological changes on the land area were analyzed by using digital elevation models (DEMs) constructed by UAV photogrammetry. The changes beneath sea level were analyzed by echo sounders. As a result, the land area showed a trend of erosion with beach scarp, and the beneath the sea water a salient was formed toward the breakwaters, which was consistent with the result of numerical simulation by using XBeach. The numerical analysis implied that the formation mechanism of beach scarp was a result of avalanching on steep slope mainly because of erosion effect amplified by water level rise behind the breakwaters. It can be identified that the formation of beach scarp was caused by high wave event and initial steep slope.

The environmental load of telecommunication service provision is increasing due to the increase in communication traffic. Virtual networks have recently begun to spread, and flexible virtual network control is expected to reduce the operating costs of telecommunication services. This paper proposes a control method to achieve both reduced power bills and stable network operation when the electricity unit price differs among areas and time periods. To begin with, the problem to minimize power bills is formulated, and to solve it quickly, a heuristic search method is proposed that utilizes network centrality. In addition, we formulate a multi-objective optimization problem characterized by parameter normalization, and simulation results show that the proposed control method can reduce power bills while suppressing the number of network reconfigurations.

The purpose of the paper is to analyse and compare the possible future parameters of four extreme cyclonic storms (Nargis in 2008, Haiyan in 2013, Gudrun in 2005, St. Jude 2013) as they would occur in the end of 21stcentury under warming climatic conditions. Using a modeling system composed of the Weather Research and Forecasting (ARW-WRF) atmospheric model, Finite Volume Community Ocean Model (FVCOM), and surrogate background conditions taken from Coupled Model Intercomparison Project (CMIP5) output in line with the IPCC proposed RCP4.5 and RCP8.5 future scenarios. The results generally showed an intensification of tropical cyclones (TCs) and corresponding increase in storm surge heights. In case of extratropical cyclones (ETCs), the future changes were either smaller or less clear.

Heavy precipitation from extratropical cyclones (ETCs) can have serious environmental and societal impacts. The aim of the study is to model changes in ETC-related precipitation in the Baltic Sea area by the end of 21stcentury. Using the Weather Research and Forecasting model (ARW-WRF), Coupled Model Intercomparison Project (CMIP5) ensemble output, the IPCC proposed RCP8.5 future scenario, and two hindcasted ETCs (Jan 2005, Nov 2008), we study these storms in projected future (i.e. "surrogate") conditions. The results showed up to 20-30% increase in precipitation; the spatial shifts and variability within the modeling domains were still substantial.