Author ORCID Identifier

Defense Date


Document Type


Degree Name

Doctor of Philosophy



First Advisor

Dr. Eyuphan Bulut


This dissertation explores how to better manage resources in mobile networks, especially for enhancing the performance of Unmanned Aerial Vehicles (UAV)-supported IoT networks. We explored ways to set up a flexible communication architecture that can handle large IoT deployments by making good use of mobile core network resources like bearers and data paths. We developed strategies that meet the needs of IoT networks and enhance network performance. We also developed and tested a system that combines traffic from several mobile devices that use the same user identity and network resources within the core mobile network. We used everyday smartphones, SIM cards, and the Amarisoft Callbox, which includes core network and eNB components, for our tests. UAVs have changed many fields due to their flexibility and versatility. This dissertation looks at how UAVs and IoT can work together, addressing important challenges to make systems work better, increase efficiency, and guarantee strong communication between UAVs and ground control stations. Collecting data efficiently from ground sensors and IoT networks is crucial, and our research is centered on planning paths that make UAVs as efficient as possible in this process. We use UAVs as relay nodes, optimizing their paths and flight plans to reduce delays and make sure data is collected and delivered on time. Additionally, we introduced a new way to route UAVs, taking into account the Age of Information (AoI) concept. We calculate AoI from when data is generated to when it is delivered through cellular-connected UAVs, making mission time as short as possible while keeping UAV connectivity. Our tests show that our heuristic approach works well in different scenarios. Utilizing UAVs as relays to facilitate communication reduces mission time and accelerates IoT data delivery, presenting an innovative advantage over alternative methods. In solving each problem, we first use an Integer Linear Programming (ILP) solution and then introduce a faster heuristic algorithm to save time. This combination ensures strong solutions while also providing quicker computational results.


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