Drones flying in squad formation while interconnected in an ad-hoc fashion are called Flying Ad hoc Networks (FANETs). These FANETs are gathering special interests in the networking community in their deployment for different vital missions. Such missions include rescue missions in case of disasters, monitoring and border control, animal monitoring, crowd monitoring and management, etc. The main problems researched with FANETs are typically inherited from what has been done for mobile ad-hoc Networks (MANETs) and Vehicular Ad-hoc Networks (VANETs) earlier. One of the major problems is routing and forwarding gathered data towards the member(i.e., the drone) closest to the sink or the member that gateways to the Internet to reach the sink. Clustering the FANET nodes (i.e., the drones) is found to be a good solution for this problem. The preeminent contributions of this thesis include a novel grinding technique of the geolocation where FANET is deployed to perform certain tasks, a grid-based mobility model for UAVs, and extending the EMASS algorithm so that it can adapt to our proposed grid-based system. The result proves our mobility model’s superiority over one of the most used mobility models, Random walk.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-92690 |
| Date | January 2022 |
| Creators | Uddin, Mohammad Messbah |
| Publisher | Luleå tekniska universitet, Institutionen för system- och rymdteknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
Page generated in 0.0016 seconds