Events

Public defence in Computer Science, M.Sc. Verónica Toro Betancur

Title of the doctoral thesis: Efficient communication for heterogeneous IoT networks
Doctoral theses hanging on the wall

Opponent: Professor Ilenia Tinnirello, University of Palermo, Italy
Custos: Professor Mario Di Francesco, Aalto University School of Science, Department of Computer Science

The thesis is publicly displayed 10 days before the defence in the publication archive Aaltodoc of Aalto University.

Electronic thesis

Public defence announcement:

Modern wireless communications typically comprise a large number of devices that intrinsically experience heterogeneous conditions. For instance, the different locations of the devices already entail heterogeneity in the network, as devices experience different environmental conditions. Moreover, networks need to often share resources with other networks that operate independently and with different communication technologies. Enabling a direct communication link between such heterogeneous technologies is imperative to share resources fairly. Furthermore, freshness of information and the time taken to deliver data to each individual device play and important role in applications that rely on timely data, which are increasingly more important nowadays. New solutions must account for different types of heterogeneity present in the networks to exploit their potential optimally. 

This dissertation addresses the challenges arising from the different dimensions of heterogeneity outlined above. It specifically proposes novel approaches that target the generation, distribution and collection of information, with particular focus on applications in the Internet of Things (IoT). We develop scalable and reliable solutions for the distribution of software updates in IoT networks; the establishment of communication links between heterogeneous technologies; the distributed optimization of LoRa networks, and the definition of policies for information retrieval that provide a fair distribution of information.

Contact details of the doctoral student: [email protected], +358 469654486

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