CA3D: Computing Accessibility-Aware Cooperative 3D Deployment of Multiple UAVs

2026-05-18

AI Summary

This study addresses the challenge of maximizing task completion rates for ground users under stringent latency constraints by proposing a computation-accessibility-aware collaborative three-dimensional deployment strategy for multiple unmanned aerial vehicles (UAVs). The approach jointly optimizes accessible computing resources, task completion probability, and redundant coverage, and for the first time reveals and formally models the fundamental trade-off between UAV inter-distance, computation accessibility, and task success. Through theoretical analysis, heterogeneous computing node modeling, and coordinated deployment optimization, the proposed method significantly outperforms baseline strategies in both hotspot and randomly distributed user scenarios: it achieves near-100% task completion in hotspot regions—approximately 3.3 times higher than random deployment—and maintains a 35% improvement over the best-performing baseline under random user distributions.

Abstract

This letter investigates computing-accessibility-aware cooperative 3D deployment of multiple UAVs for task completion enhancement, termed CA3D. We first provide a theoretical analysis showing that computing accessibility is the key mechanism linking UAV deployment to delay-constrained task completion, and that UAV inter-spacing creates a fundamental tradeoff between computing-resource accessibility and task completion. We then develop a cooperative 3D deployment design that jointly balances accessible computing capacity, task completion probability, and redundant UAV overlap. Simulation results under heterogeneous computing node capacities show that CA3D consistently outperforms Random, Fixed, and Greedy deployment baselines under both hotspot and random ground user (GU) distributions. Under the hotspot GU distribution, CA3D achieves nearly full task completion, improving the task completion probability by about 3.3x over Random deployment when the number of UAVs is 8. Under a more challenging random GU distribution, CA3D still achieves about 35% higher task completion probability than the best baseline when the number of UAVs is 12. These results demonstrate that computing-accessibility-aware cooperative 3D deployment improves not only task completion but also robustness to GU distribution changes.

Problem

• UAV deployment
• computing accessibility
• task completion
• 3D deployment
• delay-constrained tasks

Innovation

• computing accessibility
• cooperative 3D deployment
• multi-UAV systems
• task completion probability
• delay-constrained computing