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Tesi etd-02032016-132656


Thesis type
Tesi di laurea magistrale
Author
CAPPONI, ANDREA
URN
etd-02032016-132656
Title
An Energy-Efficient Framework for Data Collection Optimization in Mobile Crowd Sensing Systems
Struttura
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
INGEGNERIA DELLE TELECOMUNICAZIONI
Commissione
relatore Prof. Giordano, Stefano
correlatore Kliazovich, Dzmitry
correlatore Fiandrino, Claudio
Parole chiave
  • Mobile Crowd Sensing
  • Data Collection
  • Optimization
  • Opportunistic Sensing
  • Internet of Things
Data inizio appello
25/02/2016;
Consultabilità
parziale
Data di rilascio
25/02/2019
Riassunto analitico
Mobile crowd sensing received significant attention in the recent years and has become a popular paradigm for sensing. It operates relying on the rich set of built-in sensors equipped in mobile devices such as smartphones, tablets and wearable devices. For being effective, MCS systems require a large number of users to contribute data. While several studies focus on developing efficient incentive mechanisms to foster user participation, data collection policies still require investigation efforts. In this thesis I propose a novel distributed and sustainable framework for gathering information in cloud-based opportunistic mobile crowd sensing systems. This framework minimizes the cost of both sensing and reporting while maximizing at the same time the utility of data collection, i.e. the quality of contributed information. The proposed framework is evaluated for data collection both analytically and through simulations performed in a real urban environment and with a large number of participants.
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