Abstract
Autonomous Underwater Vehicles (AUVs) are widely used as a cost-effective mean to carry out underwater missions. During long-term missions, AUVs may collect large amounts of data that usually needs to be sent to shore. An AUV may have to travel several kilometers before reaching an area of interest near the seafloor, thus surfacing is unpractical for most cases. Long-range underwater communications rely mostly on acoustic communications, which are characterized by very low bitrates, thus making the transfer of large amounts of data too slow. GROW is a novel solution for long-range, high bitrate underwater wireless communications between a survey unit (e.g., deep sea lander, AUV) and a central station at surface. GROW combines AUVs as data mules, short-range high bitrate wireless RF or optical communications, and long-range low bitrate acoustic communications for control. In this paper we present the Underwater Data Muling Protocol (UDMP), a communications protocol that enables the control and the scheduling of the Data Mule Units within the GROW framework. Experimental results obtained using an underwater testbed show that the use of UDMP and data mules can outperform acoustic communications, achieving equivalent throughput up to 150 times higher within the typical range of operation of the latter.

Abstract
The Blue Economy has been growing in sectors such as offshore renewable energy, aquaculture, marine biotechnology, and deep sea mining. However, suitable wireless and mobile communications are lacking offshore. On the one hand, there is no coverage from terrestrial networks; on the other hand, satellite communications are still narrowband and expensive. Recently, the use of multi-hop airborne communications has been proposed to extend the coverage from terrestrial networks offshore but the communications range of these solutions is highly dependent on the height of the communications nodes. In this paper, we study the RF signal propagation in the maritime environment when the height of the receiver is changed and propose a position control approach for airborne multi-hop networks that maximizes the network capacity by taking full advantage of the signal reflections on the sea surface. The results obtained show that the proposed approach can provide lower propagation losses and higher network throughputs than random or fixed height approaches.

Abstract
Electric Vehicles (EVs) sales are increasing in the recent years due to several factors such as cost reduction, fuel cost increase, pollution reductions, government incentives, among others. At the same time, Intelligent Transportation Systems (ITS) are continuously improving, and researchers use different simulators in order to test their proposals before implementing them in real devices. However, traditional communications-aimed simulations do not include fuel consumption issues that are a key factor in transportation systems. This paper presents the addition of Electric Vehicles consumption to the ns-3 simulator, which currently is one of the most used network simulators. Our proposal follows all the models, coding style, as well as engineering guidelines of ns-3, coupled with the characteristics of each vehicle, to accurately estimate the energy consumption. We also analyze the performance of our proposal while simulating a part of the E313 highway, located in Antwerp, Belgium. In particular, we compare the ns-3 results obtained in terms of energy consumption to those obtained in SUMO. In addition, we study the impact of our proposal on the overall simulation time.

Abstract
In wireless networking R&D we typically depend on simulation and experimentation to evaluate and validate new networking solutions. While simulations allow full control over the scenario conditions, real-world experiments are influenced by external random phenomena and may produce hardly repeatable and reproducible results, impacting the validation of the solution under evaluation. Previously, we have proposed the Trace-based Simulation (TS) approach to address the problem. TS uses traces of radio link quality and position of nodes to accurately reproduce past experiments in ns-3. Yet, in its current version, the TS approach is not compatible with scenarios where the radio spectrum is shared with concurrent networks, as it does not reproduce their channel occupancy. In this paper, we introduce the InterferencePropagationLossModel and a modified MacLow to allow reproducing the channel occupancy observed in past experiments using Wi-Fi. To validate the proposed models, the network throughput was measured in different experiments performed in the w-iLab.t testbed, controlling the channel occupancy introduced by concurrent networks. The experimental results were then compared with the network throughput achieved using the improved TS approach, the legacy TS approach, and pure simulation, validating the new proposed models and confirming their relevance to reproduce experiments previously executed in real environments. © 2020 ACM.

Abstract
Besides the large amount of traffic that radio access and backhaul networks need to accommodate, the interest in low-latency communications is emerging. The goal is to reliably transmit high bitrates through the network under controlled delays, thus enabling human and machine-oriented communications. A critical aspect that must be addressed is the latency introduced by network queues. The literature has been focused on studying the queue size in wired networks, but wireless networks bring up additional challenges due to their dynamic characteristics. The problem is exacerbated in high dynamic networks, such as Flying Networks (FNs) composed of Unmanned Aerial Vehicles (UAVs), which have emerged to provide communications anywhere, anytime. The main contribution of this paper is a Proactive Queue Management (PQM) solution for FNs with controlled topology. PQM takes advantage of the knowledge of the future FN topologies and the offered traffic to define in advance the queue size of the communications nodes over time, in order to maximize the throughput with stochastic delay guarantees. The FN performance achieved using PQM is evaluated by means of ns-3 simulations, showing gains regarding aggregate throughput and average delay.

Abstract
In the past years, INESC TEC has been working on using ns-3 to reduce the gap between Simulation and Experimentation. Two major contributions resulted from our work: 1) the Fast Prototyping development process, where the same ns-3 protocol model is used in a real experiment; 2) the Trace-based Simulation (TS) approach, where traces of radio link qualities and position of nodes from past experiments are injected into ns-3 to achieve repeatable and reproducible experiments. In this paper we present ns-3 NEXT, our vision for ns-3 to enable simulation and experimentation using the same platform. We envision ns-3 as the platform that can automatically learn from past experiments and improve its accuracy to a point where simulated resources can seamlessly replace real resources. At that point, ns-3 can either replace a real testbed accurately (Offline Experimentation) or add functionality and scale to testbeds (Augmented Experimentation). Towards this vision, we discuss the current limitations and propose a plan to overcome them collectively within the ns-3 community. © 2019 ACM.