ACO, FANET, Greedy Algorithm, QoS Routing
Flying Ad-Hoc Networks (FANETs) are designed for providing seam- less connectivity between mobile devices in both air and ground level communications. The problem of neighbor discovery and data exchange relies on the availability and distribution of the infrastructure units. This limits the available routes in communicating the neighbors in mobile environments. This project introduces a novel quality of service (QoS) routing for improving the efficiency of FANETs. In this routing, the conventional ant colony optimization (ACO) and greedy methods are integrated for providing improved routing. ACO agents are responsible for discovering optimal routes to the destination whereas the greedy method filters the QoS defacing factors for improving the routing solution. The ant agents identify local solutions through periodic pheromone update and generate maximum possible solutions. In the greedy filtering process, the QoS factors are identified and the best-afford nodes are used for routing and transmission. The delay and congestion factors are used for determining best-afford route using the greedy process. The number of ACO solutions is refined based on the QoS output in the destination that makes up the best solution. The above processes are recurrent until the transmission between the source and destination is successful with better QoS.
Article Details
Unique Paper ID: 151458

Publication Volume & Issue: Volume 8, Issue 1

Page(s): 140 - 147
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