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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.

Interest
Topics
Details

Details

030
Publications

2020

Height Optimization in Aerial Networks for Enhanced Broadband Communications at Sea

Authors
Teixeira, FB; Campos, R; Ricardo, M;

Publication
IEEE Access

Abstract

2020

On the Reproduction of Real Wireless Channel Occupancy in ns-3

Authors
Cruz, R; Fontes, H; Ruela, J; Ricardo, M; Campos, R;

Publication
CoRR

Abstract

2019

Improving ns-3 Emulation Performance for Fast Prototyping of Routing and SDN Protocols: Moving Data Plane Operations to Outside of ns-3

Authors
Fontes, H; Cardoso, T; Campos, R; Ricardo, M;

Publication
Simulation Modelling Practice and Theory

Abstract

2019

A Comprehensive Study On Enterprise Wi-Fi Access Points Power Consumption

Authors
Silva, P; Almeida, NT; Campos, R;

Publication
IEEE Access

Abstract

2019

Energy Consumption Management for Dense Wi-Fi Networks

Authors
Silva, P; Almeida, NT; Campos, R;

Publication
IFIP Wireless Days

Abstract
Wi-Fi networks lack energy consumption management mechanisms. In particular, during nighttime periods, the energy waste may be significant, since all Access Points (APs) are kept switched on even though there is minimum or null traffic demand. The fact that more than 80% of all wireless traffic is originated or terminated indoor, and served by Wi-Fi, has led the scientific community to look into energy saving mechanisms for Wi-Fi networks. State of the art solutions address the problem by switching APs on and off based on manually inserted schedules or by analyzing real-time traffic demand. The first are vendor specific; the second may induce frequent station (STA) handoffs, which has an impact on network performance. The lack of implementability of solutions is also a shortcoming in most works.We propose an algorithm, named Energy Consumption Management Algorithm (ECMA), that learns the daytime and nighttime periods of the Wi-Fi network. ECMA was designed having in mind its implementability over legacy Wi-Fi equipment. At daytime, the radio interfaces of the AP (2.4 GHz and 5 GHz) are switched on and off automatically, according to the traffic demand. At nighttime, clusters of APs, covering the same area, are formed, leaving one AP always switched on for basic coverage and the redundant APs swichted off to maximize energy savings, while avoiding coverage and performance hampering. Simulation results show energy savings of up to 50% are possible using the ECMA algorithm. © 2019 IEEE.

Supervised
thesis

2019

Using Machine Learning to Improve Performance of Flying Networks

Author
Baltasar de Vasconcelos Dias Aroso

Institution
UP-FEUP

2019

Improving the performance evaluation of wireless networks: towards a simulation-experimentation synergy using ns-3

Author
Hélder Martins Fontes

Institution
UP-FEUP

2019

Data Muling for Broadband and Long Range Wireless Underwater Communications

Author
Nuno Francisco Monteiro de Barros Moreira

Institution
UP-FEUP

2019

Routing for Flying Networks using Software-Defined Networking

Author
André Duarte Correia de Oliveira

Institution
UP-FEUP

2019

Green Wireless Video Sensor Networks using a Low-Power Control Channel

Author
Filipe Miguel Monteiro da Silva e Sousa

Institution
UP-FEUP