Abstract
The combination of unmanned aerial vehicles (UAVs) and mobile edge computing (MEC) technology breaks through the limitations of traditional terrestrial communications. The effective line-of-sight channel provided by UAVs can greatly improve the communication quality between edge servers and mobile devices (MDs). To further enhance the Quality-of-Service (QoS) of MEC systems, a multi-UAV-enabled MEC system model is designed. In the proposed model, UAVs are regarded as edge servers to offer computing services for MDs, aiming to minimize the average task response time by jointly optimizing UAV deployment and computation offloading. Based on the problem definition, a two-layer joint optimization method (PSO-GA-G) is proposed. First, the outer layer utilizes a Particle Swarm Optimization algorithm combined with Genetic Algorithm operators (PSO-GA) to optimize UAV deployment. Next, the inner layer adopts a greedy algorithm to optimize computation offloading. The extensive simulation experiments verify the feasibility and effectiveness of the proposed PSO-GA-G. The results show that the PSO-GA-G can achieve a lower average task response time than the other three baselines.
Highlights
With the rapid development of the Internet-of-Things (IoT) and the fifth-generation (5G) communication technology, numerous emerging mobile applications, such as unmannedTraditional mobile communications rely on ground communication infrastructures [5]
Zhang and Ansari [30] developed an approximation algorithm to improve the average user latency in unmanned aerial vehicles (UAVs)-aided mobile edge computing (MEC) networks. Different from these researches, our work aims to minimize the average task response time in a multi-UAVenabled MEC system by jointly optimizing UAV deployment and computation offloading
In multi-UAV-enabled MEC systems, the response time of the computing tasks from mobile devices (MDs) can be greatly reduced by deploying UAVs to provide computation offloading services
Summary
With the rapid development of the Internet-of-Things (IoT) and the fifth-generation (5G) communication technology, numerous emerging mobile applications, such as unmanned. Traditional mobile communications rely on ground communication infrastructures [5]. In some isolated areas (e.g., mountains and oceans) or some emergencies (e.g., disaster relief and military exercises), the restricted ground communication infrastructures may have a huge. Due to the high flexibility, strong mobility, and low deployment cost, unmanned aerial vehicles (UAVs) are gradually applied to the field of emergency communications [7]. UAVs can be regarded as mobile base stations to provide communication services for MDs on the ground, thereby building an integrated ground-air communication network [8]. UAVs can flexibly change their deployment positions in the network. When MD or network status changes, UAVs can be quickly adjusted at a lower cost
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