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About

Education: PhD in Computer Science, Faculdade de Ciências da Universidade do Porto, 2011.

Research interests: concurrency, software verification and testing, unmanned vehicle networks

Selected publications:

Short bio

  • Currently researcher at CRACS/INESC-TEC, Prof. Auxiliar Convidado 25% FCUP
  • 2012-2016: Prof. Auxiliar Convidado c/dedicação exclusiva, FCUL 
  • 2006-2011: PhD student in Computer Science, FCUP
  • 1998-2005: Software engineer/programmer for consulting companies (Portugal and Brazil)
  • 1998: MSc in Advanced Computing, Imperial College London
  • 1997: BSc in Computer Science (pre-Bologne), FCUP

Interest
Topics
Details

Details

  • Name

    Eduardo Brandão Marques
  • Cluster

    Computer Science
  • Role

    Senior Researcher
  • Since

    01st April 2016
003
Publications

2021

Energy-aware adaptive offloading of soft real-time jobs in mobile edge clouds

Authors
Silva, J; Marques, ERB; Lopes, LMB; Silva, F;

Publication
JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS

Abstract
We present a model for measuring the impact of offloading soft real-time jobs over multi-tier cloud infrastructures. The jobs originate in mobile devices and offloading strategies may choose to execute them locally, in neighbouring devices, in cloudlets or in infrastructure cloud servers. Within this specification, we put forward several such offloading strategies characterised by their differential use of the cloud tiers with the goal of optimizing execution time and/or energy consumption. We implement an instance of the model using Jay, a software framework for adaptive computation offloading in hybrid edge clouds. The framework is modular and allows the model and the offloading strategies to be seamlessly implemented while providing the tools to make informed runtime offloading decisions based on system feedback, namely through a built-in system profiler that gathers runtime information such as workload, energy consumption and available bandwidth for every participating device or server. The results show that offloading strategies sensitive to runtime conditions can effectively and dynamically adjust their offloading decisions to produce significant gains in terms of their target optimization functions, namely, execution time, energy consumption and fulfilment of job deadlines.

2020

Ramble: Opportunistic Crowdsourcing of User-Generated Data using Mobile Edge Clouds

Authors
Garcia, M; Rodrigues, J; Silva, J; Marques, ERB; Lopes, LMB;

Publication
2020 Fifth International Conference on Fog and Mobile Edge Computing (FMEC)

Abstract

2020

Jay: Adaptive Computation Offloading for Hybrid Cloud Environments

Authors
Silva, J; Marques, ERB; Lopes, LMB; Silva, F;

Publication
2020 Fifth International Conference on Fog and Mobile Edge Computing (FMEC)

Abstract

2018

Video Dissemination in Untethered Edge-Clouds: A Case Study

Authors
Rodrigues, J; Marques, ERB; Silva, J; Lopes, LMB; Silva, F;

Publication
Distributed Applications and Interoperable Systems - Lecture Notes in Computer Science

Abstract

2018

Flux

Authors
Silva, N; Marques, ERB; Lopes, LMB;

Publication
ACM Transactions on Sensor Networks

Abstract

Supervised
thesis

2020

Scheduling Computations Over High Churn Networks of Mobile Devices

Author
Joaquim Magalhães Esteves da Silva

Institution
UP-FCUP

2020

Application Security in Continuous Delivery

Author
Fábio Daniel Santos Freitas

Institution
UP-FCUP

2020

A Portuguese Flora Identification Tool Using Deep Learning

Author
Miguel Ângelo Ribeiro Marques

Institution
UP-FCUP

2020

Property-based testing of ERC-20 smart contracts

Author
Célio Gil Gouveia Rodrigues

Institution
UP-FCUP

2019

Plataforma de Monitorização da Biodiversidade no Concelho de Gaia

Author
Ricardo André Freitas Santos

Institution
UP-FCUP