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Group Mobility Models Drone Swarm Networks

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dc.contributor.author Rafai, Faraz Saleem
dc.date.accessioned 2023-08-15T09:48:40Z
dc.date.available 2023-08-15T09:48:40Z
dc.date.issued 2023
dc.identifier.other 325397
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/36557
dc.description Supervisor: Dr. Muhammad Umar Farooq en_US
dc.description.abstract Group Mobility Models (GMM) Drone Swarm Networks is an emerging technology with manifold requirement in modern warfare and surveillance[1] means. Architectures of various drone swarm networks were studied with their practical efficacy to cater for future requirements in defence, agriculture, surveillance[1], security, searching, disaster management[5], logistics chain management with main focus on proposing of Hybrid GMM for search and pursuit of a target[30] in a region. The proposed Mobility Model is combination of existing two mobility models i.e. Column Mobility Model and Pursue Mobility Model. The proposed GMM has been implemented using network simulation tool NS2[2] besides BonnMotion[3] open-source software for investigating various mobility models and even generating mobility files before proposing the subject model. Column Mobility Model will help in extensive search of the area or a region using Drone Swarms as Swarm will be divided in various columns/ subgroups for better coverage while Pursue Mobility Model will be individual drone response after the target has been detected for tracking and trailing the target. The Drone Swarm Networks can use this Hybrid model to effectively search and pursue a target like Police search and pursue criminals after crime scene or like Armed Forces including Army and Airforce scout and pursue terrorists after any miscreant attack. Performance of routing protocols[4] AODV and OLSR was evaluated in proposed mobility model using various performance metrics like average end-to-end delay, average throughput, total dropped packets, packet delivery ratio and even retransmitted packets to ascertain how it will behave with regards to scalability of the swarm, performance impact of frequent agile movements in pursue behavior and searching movements in column behavior, network congestion and traffic. AODV performed better than OLSR with regards to all mentioned performance metrics in proposed GMM. Therefore, the proposed model was implemented for search and pursuit operations by Drone Swarm Networks using AODV routing protocol[4]. en_US
dc.language.iso en en_US
dc.publisher College of Electrical & Mechanical Engineering (CEME), NUST en_US
dc.subject Group Mobility Model(GMM), Pursue Mobility Model, Column Mobility Model, AODV, OLSR, NS2[2], BonnMotion[3], Drone Swarm Networks en_US
dc.title Group Mobility Models Drone Swarm Networks en_US
dc.type Thesis en_US


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