Edinburgh Napier University

  Drones can be used in many assistance roles in complex communication situations and play key roles as aerial wireless relays to help terrestrial network communications. Although a great deal of emphasis has been placed on the drone-assisted networks, the majority of existing works often focus on routing protocols and do not fully exploit the drones’ superiority and flexibility. To fill in this gap, this paper proposes a collaborative communication scheme for multiple drones to assist the urban vehicular ad-hoc networks (VANETs). In this scheme, drones are distributed according to the predicted terrestrial traffic condition in order to efficiently alleviate the inevitable problems of conventional VANETs, such as building obstacle, isolated vehicles, and uneven traffic loading. To effectively coordinate multiple drones simultaneously, this issue is modeled as a multimodal optimization problem to improve the global performance on a certain space. To this end, a succinct swarm-based optimization algorithm, namely Multimodal Nomad Algorithm (MNA) is presented. This algorithm is inspired by the migratory behavior of the nomadic tribes on Mongolia grassland. Based on a real-world floating car data of Chengdu city in China, extensive experiments are carried out to examine the performance of the proposed MNA-optimized drone-assisted VANET considering the processed mobility models. The results demonstrate that our scheme outperforms its counterparts in terms of the average number of hops, improved average packet delivery ratio, and throughput of the global test space.