{"ID":2862458,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.25700","arxiv_id":"2509.25700","title":"PAST: Pilot and Adaptive Orchestration for Timely and Resilient Service Delivery in Edge-Assisted UAV Networks under Spatio-Temporal Dynamics","abstract":"Incentive-driven resource trading is essential for UAV applications with intensive, time-sensitive computing demands. Traditional spot trading suffers from negotiation delays and high energy costs, while conventional futures trading struggles to adapt to the dynamic, uncertain UAV-edge environment. To address these challenges, we propose PAST (pilot-and-adaptive stable trading), a novel framework for edge-assisted UAV networks with spatio-temporal dynamism. PAST integrates two complementary mechanisms: PilotAO (pilot trading agreements with overbooking), a risk-aware, overbooking-enabled early-stage decision-making module that establishes long-term, mutually beneficial agreements and boosts resource utilization; and AdaptAO (adaptive trading agreements with overbooking rate update), an intelligent adaptation module that dynamically updates agreements and overbooking rates based on UAV mobility, supply-demand variations, and agreement performance. Together, these mechanisms enable both stability and flexibility, guaranteeing individual rationality, strong stability, competitive equilibrium, and weak Pareto optimality. Extensive experiments on real-world datasets show that PAST consistently outperforms benchmark methods in decision-making overhead, task completion latency, resource utilization, and social welfare. By combining predictive planning with real-time adjustments, PAST offers a valuable reference on robust and adaptive practice for improving low-altitude mission performance.","short_abstract":"Incentive-driven resource trading is essential for UAV applications with intensive, time-sensitive computing demands. Traditional spot trading suffers from negotiation delays and high energy costs, while conventional futures trading struggles to adapt to the dynamic, uncertain UAV-edge environment. To address these cha...","url_abs":"https://arxiv.org/abs/2509.25700","url_pdf":"https://arxiv.org/pdf/2509.25700v1","authors":"[\"Houyi Qi\",\"Minghui Liwang\",\"Liqun Fu\",\"Sai Zou\",\"Xinlei Yi\",\"Wei Ni\",\"Huaiyu Dai\"]","published":"2025-09-30T02:58:58Z","proceeding":"cs.DC","tasks":"[\"cs.DC\",\"cs.GT\",\"cs.NI\"]","methods":"[]","has_code":false}