Geographically distributed wireless networks, and in particular wireless sensor networks (WSNs), present specific challenges in the efficient management of data collection and transmission. This thesis carries out an analytical-comparative study focused on hierarchical routing protocols and on the integration between WSNs and unmanned aerial vehicles (UAVs). These solutions enable the optimization of data transmission in large and complex environments, addressing critical issues related to energy consumption, scalability, and network reliability. Special attention is given to the use of UAVs as "data mules" to reduce overall traffic and improve system efficiency, including the optimization of UAV flight trajectories through machine learning techniques.
Le reti wireless geograficamente distribuite, e in particolare le reti di sensori wireless (WSN), presentano delle problematiche particolari nella gestione efficiente della raccolta e della trasmissione dei dati. In questa tesi, viene effettuato un lavoro di tipo analitico-comparativo, focalizzato sullo studio di protocolli di instradamento gerarchico e sull’integrazione tra le WSN e veicoli aerei senza pilota (UAV). Queste soluzioni permettono un'ottimizzazione della trasmissione dei dati in ambienti estesi e complessi, affrontando criticità legate al consumo energetico, alla scalabilità e all’affidabilità della rete. Viene approfondito l’uso degli UAV come “data mule” per ridurre il traffico totale e migliorare l’efficienza complessiva, che include la pianificazione delle traiettorie di volo tramite tecniche di apprendimento automatico.
Metodi di gestione di reti wireless di sensori geograficamente distribuite
PIOVESAN, MATTEO
2024/2025
Abstract
Geographically distributed wireless networks, and in particular wireless sensor networks (WSNs), present specific challenges in the efficient management of data collection and transmission. This thesis carries out an analytical-comparative study focused on hierarchical routing protocols and on the integration between WSNs and unmanned aerial vehicles (UAVs). These solutions enable the optimization of data transmission in large and complex environments, addressing critical issues related to energy consumption, scalability, and network reliability. Special attention is given to the use of UAVs as "data mules" to reduce overall traffic and improve system efficiency, including the optimization of UAV flight trajectories through machine learning techniques.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/87139