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About

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
001
Publications

2018

Video Dissemination in Untethered Edge-Clouds: A Case Study

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

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

2018

Programming Networked Vehicle Systems Using Dolphin - Field Tests at REP'17

Authors
Lima, K; Marques, ERB; Pinto, J; Sousa, JB;

Publication
2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO)

Abstract

2018

Dolphin: a task orchestration language for autonomous vehicle networks

Authors
Lima, K; Marques, ERB; Pinto, J; Sousa, JB;

Publication
CoRR

Abstract

2018

FLUX: A Platform for Dynamically Reconfigurable Mobile Crowd-Sensing

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

Publication
ACM TRANSACTIONS ON SENSOR NETWORKS

Abstract
FLUX is a platform for dynamically reconfigurable crowd-sensing using mobile devices like smartphones and tablets, programmed under a notion of region-based sensing. Each region is defined by a set of physical constraints that determine the sensing scope, e.g., based on device position or other environmental variables, plus a set of periodic tasks that perform the actual sensing. The resulting behavior is inherently dynamic: as a device's state changes, e.g., moves in space, it enters and/or leaves different regions, thereby changing the set of active tasks; moreover, regions can be added, deleted, and reprogrammed on-the-fly. FLUX makes use of a domain-specific language for sensing tasks that is compiled into abstract bytecode, later executed by a low-footprint virtual machine within a device, guaranteeing runtime safety by construction. For region/task dissemination, FLUX employs a broker that holds a changeable region configuration plus gateways that mirror the configuration throughout different network access points to which devices connect. Sensing data is streamed by devices to gateways and then back to the broker. Live or archived data streams are in turn fed by the broker to data-processing clients, which interface with the broker using a publish/subscribe API. We conducted two case-study experiments illustrating FLUX: a single-region deployment to monitor WiFi signal quality, and a multi-region deployment to monitor noise, temperature, and places-of-interest based on device movement.