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Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-05072025-114500


Tipo di tesi
Tesi di laurea magistrale
Autore
IMBELLI CAI, MARCO
URN
etd-05072025-114500
Titolo
Computation offloading and energy consumption in the Internet of Things: a structured approach
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
COMPUTER ENGINEERING
Relatori
relatore Vecchio, Alessio
correlatore Luconi, Valerio
Parole chiave
  • computation offloading
  • edge computing
  • energy consumption
  • Internet of Things
  • wearable device
Data inizio appello
27/05/2025
Consultabilità
Completa
Riassunto
Internet of Things (IoT) and wearable devices often have limited energy budgets and reduced computing resources. Continuously running an application on a smartwatch, for example, can quickly drain its battery life, resulting in an unsatisfactory user experience. Computation offloading, i.e. transferring computationally intensive tasks to more powerful devices in the edge-cloud continuum, can help reduce the power needs of IoT and wearable devices, possibly extending their battery life.
In this thesis, the application running on resource-constrained devices is structured as a set of functions that can be relocated on the edge according to a serverless approach.
The ultimate goal is to determine whether this paradigm can be useful in optimizing a wearable device's battery life and performance.
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