AirCompSim: A Discrete Event Simulator for Air Computing

TL;DR

AirCompSim introduces a modular discrete-event simulator to evaluate air computing environments that leverage LAP, HAP, and LEO platforms for dynamic QoS. It provides a five-module architecture (Simulation, Server, User, Application, Mobility) plus Scenario and DRL modules, enabling DRL-driven UAV policies and reproducible, logged experiments. The paper demonstrates dynamic capacity enhancement experiments showing how UAV count and user load affect task success rate, service time, and resource utilization, with offloading patterns shifting among edge, UAV, and cloud. Overall, AirCompSim offers a practical testbed for systematic performance evaluation and policy testing in 3D-networked edge environments for air computing.

Abstract

Air components, including UAVs, planes, balloons, and satellites have been widely utilized since the fixed capacity of ground infrastructure cannot meet the dynamic load of the users. However, since those air components should be coordinated in order to achieve the desired quality of service, several next-generation paradigms have been defined including air computing. Nevertheless, even though many studies and open research issues exist for air computing, there are limited test environments that cannot satisfy the performance evaluation requirements of the dynamic environment. Therefore, in this study, we introduce our discrete event simulator, AirCompSim, which fulfills an air computing environment considering dynamically changing requirements, loads, and capacities through its modular structure. To show its capabilities, a dynamic capacity enhancement scenario is used for investigating the effect of the number of users, UAVs, and requirements of different application types on the average task success rate, service time, and server utilization. The results demonstrate that AirCompSim can be used for experiments in air computing.

Figures (8)

• Figure 1: An air computing environment.
• Figure 2: Relationship of the AirCompSim modules.
• Figure 3: Distribution and coverage of edge servers in the example scenario.
• Figure 4: Average task success rate.
• Figure 5: Average service time.