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Sobre

Sobre

Rui Campos tem doutoramento em Engenharia Electrotécnica e de Computadores pela Universidade do Porto desde 2011. Atualmente, é coordenador da área de redes sem fios (http://win.inesctec.pt) no Centro de Telecomunicações e Multimédia composta por 30 investigadores, e é membro sénior do IEEE. Rui Campos tem vindo a coordenadar vários projetos de I&D+i, incluindo: SIMBED, UGREEN, BLUECOM+, MareCom, MTGrid, a ação WiFIX dentro do projeto FP7 CONFINE, Mare-Fi, Under-Fi, ReCoop e HiperWireless. Rui Campos tem igualmente participado em múltiplos projetos de I&D, incluindo os seguintes projetos europeus: H2020 RAWFIE, FP7 SUNNY, FP7 CONFINE, FP6 Ambient Networks Phase 1 e FP6 Ambient Networks Phase 2. Os seus interesses de investigação incluem os aspetos de controlo de acesso ao meio, gestão de recursos rádio, gestão de mobilidade e auto-configuração em redes emergentes, com especial foco nas redes formadas por plataformas voadoras, redes marítimas e redes subaquáticas. 

Tópicos
de interesse
Detalhes

Detalhes

033
Publicações

2022

Joint Energy and Performance Aware Relay Positioning in Flying Networks

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

Publicação
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

Placement and Allocation of Communications Resources in Slicing-aware Flying Networks

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

Publicação
17th Wireless On-Demand Network Systems and Services Conference, WONS 2022, Oppdal, Norway, March 30 - April 1, 2022

Abstract

2022

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

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

Publicação
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

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

Publicação
AD HOC NETWORKS

Abstract

2021

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

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

Publicação
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.

Teses
supervisionadas

2021

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

Autor
Gonçalo Regueiras dos Santos

Instituição
UP-FEUP

2021

High Definition Wireless Video Streaming using Underwater Data Mules

Autor
João Pedro Teixeira Loureiro

Instituição
UP-FEUP

2021

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

Autor
Agostinho Filipe de Almeida Coimbra Maia

Instituição
UP-FEUP

2021

Connect the dots: automation in investigative jornalism workflow

Autor
Joana Rodrigues da Silva

Instituição
UP-FEUP

2020

Centralized Routing for Flying Backhaul Networks

Autor
André Filipe Coelho

Instituição
UP-FEUP