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About

Rui Campos has a PhD degree in Electrical and Computers Engineering in 2011, from University of Porto. Currently, he leads the “Wireless Networks” research area (http://win.inescporto.pt) of the Centre for Telecommunications and Multimedia consisting of 30 researchers, and he is an IEEE Senior Member. He has coordinated several research projects, including: SIMBED in Fed4FIRE+ Open Call 3, UGREEN, BLUECOM+, MareCom, MTGrid, the WiFIX action approved in CONFINE Open Call 1, Mare-Fi, Under-Fi, ReCoop, and HiperWireless. Rui Campos has participated in several research projects, including the following European projects: H2020 Fed4FIRE+, H2020 RAWFIE, FP7 SUNNY, FP7 CONFINE, FP6 Ambient Networks Phase 1, and FP6 Ambient Networks Phase 2. His research interests include medium access control, radio resource management, mobility management, and network auto-configuration in emerging wireless networks, with special focus on flying networks, maritime networks, and underwater networks.

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Details

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033
Publications

2022

Joint Energy and Performance Aware Relay Positioning in Flying Networks

Authors
Rodrigues, H; Coelho, A; Ricardo, M; Campos, R;

Publication
IEEE ACCESS

Abstract
<p>Unmanned Aerial Vehicles (UAVs) have emerged as suitable platforms for transporting and positioning communications nodes on demand, including Wi-Fi Access Points and cellular Base Stations. This paved the way for the deployment of flying networks capable of temporarily providing wireless connectivity and reinforcing the coverage and capacity of existing networks anywhere, anytime. Several solutions have been proposed in the literature for the positioning of UAVs that act as Flying Access Points (FAPs). Yet, the positioning of Flying Communications Relays (FCRs) in charge of forwarding the traffic to/from the Internet has not received equal attention. A major challenge in flying networks is the UAVs endurance. Since the UAVs are typically powered by on-board batteries with limited capacity, whose energy is used for communications and propulsion, the UAVs need to land frequently for recharging or replacing their batteries, limiting the flying network availability. State of the art works are focused on optimizing both the flying network performance and the energy-efficiency from the communications point of view, but do not consider the energy spent for the UAV propulsion. Yet, the energy spent for communications is typically negligible when compared with the energy spent for the UAV propulsion.</p><p>In order to address the FCR UAV positioning and energy-efficiency challenges, we have proposed the Energy-aware RElay Positioning (EREP) algorithm. EREP defines the trajectory and speed of the FCR UAV that minimize the energy spent for the UAV propulsion. However, since EREP considers a theoretical radio propagation model for computing the minimum Signal-to-Noise Radio (SNR) values that allow to meet the FAPs traffic demand, this may lead to network performance degradation in real-world networking scenarios, especially due to the FCR UAV movement. In this article, we propose the Energy and Performance Aware relay Positioning (EPAP) algorithm. Built upon the EREP algorithm, EPAP defines target performance-aware SNR values for the wireless links established between the FCR UAV and the FAPs and, based on that, computes the trajectory to be completed by the FCR UAV, so that the energy spent for the UAV propulsion is minimized. EPAP was evaluated in terms of both the flying network performance and the FCR UAV endurance, considering multiple networking scenarios. Simulation results show gains up to 25% in the FCR UAV endurance, while not compromising the Quality of Service offered by the flying network.</p>

2022

Machine Learning Based Propagation Loss Module for Enabling Digital Twins of Wireless Networks in ns-3

Authors
Almeida, EN; Rushad, M; Kota, SR; Nambiar, A; Harti, HL; Gupta, C; Waseem, D; Santos, G; Fontes, H; Campos, R; Tahiliani, MP;

Publication
WNS3 2022: 2022 Workshop on ns-3, Virtual Event, USA, June 22 - 23, 2022

Abstract

2021

Joint Traffic-Aware UAV Placement and Predictive Routing for Aerial Networks

Authors
Almeida, EN; Coelho, A; Ruela, J; Campos, R; Ricardo, M;

Publication
AD HOC NETWORKS

Abstract

2021

Reproducible MIMO operation in ns-3 using trace-based wi-fi rate adaptation

Authors
Lamela, V; Fontes, H; Ruela, J; Ricardo, M; Campos, R;

Publication
WNS3 2021: 2021 Workshop on ns-3, Virtual Event, USA

Abstract
Today, wireless networks are operating in increasingly complex environments, impacting the evaluation and validation of new networking solutions. Simulation, although fully controllable and easily reproducible, depends on simplified physical layer and channel models, which often produce optimistic results. Experimentation is also influenced by external random phenomena and limited testbed scale and availability, resulting in hardly repeatable and reproducible results. 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, TS is not compatible with scenarios where Multiple-In-Multiple-Out (MIMO) is used. This is especially relevant since ns-3 assumes perfectly independent MIMO radio streams. In this paper, we introduce the Trace-based Wi-Fi Station Manager Model, which is capable of reproducing the Rate Adaptation of past Wi-Fi experiments, including the number of effective radio streams used. To validate the proposed model, the network throughput was measured in different experiments performed in the w-iLab.t testbed, considering Single-In-Single-Out (SISO) and MIMO operation using IEEE 802.11a/n/ac standards. The experimental results were then compared with the network throughput achieved using the improved TS and Pure Simulation (PS) approaches, validating the new proposed model and confirming its relevance to reproduce experiments previously executed in real environments. © 2021 ACM.

2021

Traffic-aware Gateway Placement for High-capacity Flying Networks

Authors
Coelho, A; Fontes, H; Campos, R; Ricardo, M;

Publication
2021 IEEE 93RD VEHICULAR TECHNOLOGY CONFERENCE (VTC2021-SPRING)

Abstract

Supervised
thesis

2021

High Definition Wireless Video Streaming using Underwater Data Mules

Author
João Pedro Teixeira Loureiro

Institution
UP-FEUP

2021

Trace-based ns3-gym Reinforcement Learning Environment Framework for Wireless Networks

Author
Gonçalo Regueiras dos Santos

Institution
UP-FEUP

2021

An SDN-based Overlay Networking Solution for Transparent Multi-homed Vehicular Communications

Author
Agostinho Filipe de Almeida Coimbra Maia

Institution
UP-FEUP

2021

Connect the dots: automation in investigative jornalism workflow

Author
Joana Rodrigues da Silva

Institution
UP-FEUP

2020

Multi-technology Flying Access Network for Disaster Management Scenarios

Author
Rúben Miguel Rei Queirós

Institution
UP-FEUP