Alessandro D'Armiento
A distributed framework for real-time ingestion of unstructured streaming data.
Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2018
|
Preview |
PDF (Tesi_di_laurea)
- Tesi
Licenza: Creative Commons Attribution Non-commercial Share Alike. Download (2MB) | Preview |
Abstract
The explosive growth in the number of devices connected to the Internet of Things (IoT) only reflect how the growth of big data perfectly overlaps with that of IoT. The management of big data in a continuously expanding network gives rise to non-trivial concerns regarding data collection efficiency, data processing, analytics, and security. The Internet of things would encode 50 to 100 trillion objects, and be able to follow the movement of those objects. Human beings in surveyed urban environments are each surrounded by 1000 to 5000 trackable objects. In 2015 there were already 83 million smart devices, and this number is most likely intended to grow.
Challenges for producers of IoT applications are to clean, process and interpret the vast amount of data which is gathered by the sensors, along with the storage of this bulk data
Relatori
Anno Accademico
Tipo di pubblicazione
Numero di pagine
Corso di laurea
Classe di laurea
Aziende collaboratrici
URI
![]() |
Modifica (riservato agli operatori) |
