The offshore wind farms are gaining momentum due to their promise to offer sustainable energy with low pollution and greenhouse gases emission. However, despite all the immense technological progress of recent years, the operation in a harsh and hard-to-reach environment remains challenging. According to the reports, each offshore wind turbine requires five maintenance visits a year on average, and the cumulative repair costs constitute around 30% of the turbine's life-cycle expenditure. Motivated by the advancement of massive machinetype connectivity (mMTC) and satellite technologies, in this study, we investigate the potential of these to enable remote monitoring of the offshore wind farms. Specifically, the two alternative architectures are considered. The indirect architecture relies on using a local mMTC gateway (GW) with a backbone over a reliable communication channel (e.g., satellite or wire-based). The direct approach implies the transmission of the data by sensors on the wind turbines directly to the mMTC GW on the lowearth orbit (LEO) satellite. The details of the system design, the alternative implementation strategies and relevant pros, cons and trade-offs are pin-pointed. Finally, we employ simulations using realistic deployment and traffic and advanced propagation and collision models to characterize these two approaches' feasibility and packet delivery probability numerically when implemented over LoRaWAN mMTC technology.
A comparative analysis is carried out to study the unsteady flow of a Maxwell fluid in the presence of Newtonian heating near a vertical flat plate. The fractional derivatives presented by Caputo and Caputo–Fabrizio are applied to make a physical model for a Maxwell fluid. Exact solutions of the non-dimensional temperature and velocity fields for Caputo and Caputo–Fabrizio time-fractional derivatives are determined via the Laplace transform technique. Numerical solutions of partial differential equations are obtained by employing Tzou’s and Stehfest’s algorithms to compare the results of both models. Exact solutions with integer-order derivative (fractional parameter α = 1) are also obtained for both temperature and velocity distributions as a special case. A graphical illustration is made to discuss the effect of Prandtl number Pr and time t on the temperature field. Similarly, the effects of Maxwell fluid parameter λ and other flow parameters on the velocity field are presented graphically, as well as in tabular form.
Long Range-Frequency Hopping Spread Spectrum (LR-FHSS) has been recently introduced into the LoRaWAN protocol specification to increase network capacity and collision robustness, and enable direct connectivity between machine devices and the Low Earth Orbit (LEO) satellites. In this letter, we first construct the analytical and simulation models for packet delivery over LR-FHSS from ground nodes to a LEO satellite, and then use the developed analytic and simulation models to generate the numerical results. Our results reveal the potential feasibility of large-scale networks, demonstrate some trade-offs between the two new LR-FHSS-based data rates for the EU region, and reveal the key reasons for packet losses.
Low-power wide-area networks (LPWANs) are emerging rapidly as a fundamental Internet of Things (IoT) technology because of their low-power consumption, long-range connectivity, and ability to support massive numbers of users. With its high growth rate, Long-Range (LoRa) is becoming the most adopted LPWAN technology. This research work contributes to the problem of LoRa spreading factor (SF) allocation by proposing an algorithm on the basis of K-means clustering. We assess the network performance considering the outage probabilities of a large-scale unconfirmed-mode class-A LoRa Wide Area Network (LoRaWAN) model, without retransmissions. The proposed algorithm allows for different user distribution over SFs, thus rendering SF allocation flexible. Such distribution translates into network parameters that are application dependent. Simulation results consider different network scenarios and realistic parameters to illustrate how the distance from the gateway and the number of nodes in each SF affects transmission reliability. Theoretical and simulation results show that our SF allocation approach improves the network’s average coverage probability up to 5 percentage points when compared to the baseline model. Moreover, our results show a fairer network operation where the performance difference between the best- and worst-case nodes is significantly reduced. This happens because our method seeks to equalize the usage of each SF. We show that the worst-case performance in one deployment scenario can be enhanced by 1.53 times.
The maritime autonomous surface ships (MASS) promise a revolution in naval logistics by offering sustainability, safety, and operational costs reduction. The MASS can bring to Arctic and other hard-to-reach regions numerous social and economic benefits, thus contributing to equalizing the access for human and machine-terminals to connectivity, and equate the life quality of their inhabitants with that of the other regions. In this paper, we suggest a hybrid communication architecture that separates ship's data traffic into awareness and emergency components. For the former traffic, we advocate the possibility of Direct-to-Satellite (DtS) using massive machinetype communication (mMTC) and low-power wide-area network (LPWAN) technologies. To validate this hypothesis and investigate the potential performance and effect of different design and configuration parameters, we conduct simulations based on reallife positions of ships and satellites, traffic patterns, and the LoRaWAN connectivity model. Our results demonstrate the suggested approach's feasibility and clarify the different parameters' effects on the connectivity performance for the classical LoRa and novel long-range frequency hopping spread spectrum (LR-FHSS) modulation coding schemes. Notably, the combination of multiconnectivity of LoRaWAN LPWAN technology and multi-satellite visibility dramatically boosts the probability of packet delivery.
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