Abstract
<p>Drones are used for public safety missions because of their communication capabilities, unmanned mission, flexible deployment, and low cost. Recently, drone-assisted emergency communication systems in disasters have been developed where instead of a single large drone, flying ad hoc networks (FANETs) are proposed through clustering. Although cluster size has an impact on the proposed system's performance, no method is provided to effectively regulate cluster size. In this paper, optimum cluster size is obtained through two distinct meta-heuristic optimization algorithms - the Cuckoo Search Algorithm (CUCO) and the Particle Swarm Algorithm (PSO). Flowcharts and algorithms of CUCO and PSO are provided. A presentation of an analytical investigation based on the Markov chain model is provided. To further validate the analytical study, simulation results are presented. Simulation shows the improvement in terms of throughput and packet dropping rate (PDR).</p>
Keywords
Subject Areas
OpenAlex SDG Match
SDGs auto-classified by OpenAlex (score ≥ 0.4 shown).