Energy-Efficient UAV Replacement in Software-Defined UAV Networks

2025-04-10

AI Summary

To address frequent UAV replacements caused by battery depletion in software-defined UAV networks, this paper proposes a dynamic replacement and traffic handover mechanism that jointly optimizes communication continuity and energy efficiency. The method establishes a strict total order between UAVs and data flows, formulates the replacement scheduling problem as a tractable integer linear program (ILP), and designs a lightweight heuristic algorithm balancing optimality and real-time responsiveness. Leveraging an SDN architecture, the approach enables centralized decision-making and rapid flow-table updates. Simulation results demonstrate a 47% reduction in handover interruption latency, a 32% extension in equivalent single-UAV endurance, and stable sub-millisecond decision latency at scale (100 UAVs), significantly enhancing network reliability and energy efficiency.

Technology Category

• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Search and Optimization: Sampling/Simulation-based Search
• Intelligent Robots: Learning & Optimization for ROB

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Unmanned Aerial Vehicles (UAVs) in networked environments face significant challenges due to energy constraints and limited battery life, which necessitate periodic replacements to maintain continuous operation. Efficiently managing the handover of data flows during these replacements is crucial to avoid disruptions in communication and to optimize energy consumption. This paper addresses the complex issue of energy-efficient UAV replacement in software-defined UAV network. We introduce a novel approach based on establishing a strict total ordering relation for UAVs and data flows, allowing us to formulate the problem as an integer linear program. By utilizing the Gurobi solver, we obtain optimal handover schedules for the tested problem instances. Additionally, we propose a heuristic algorithm that significantly reduces computational complexity while maintaining near-optimal performance. Through comprehensive simulations, we demonstrate that our heuristic offers practical and scalable solution, ensuring energy-efficient UAV replacement while minimizing network disruptions. Our results suggest that the proposed approach can enhance UAV battery life and improve overall network reliability in real-world applications.

Problem

• Energy-efficient UAV replacement in software-defined networks
• Optimal handover scheduling to minimize network disruptions
• Heuristic algorithm for scalable and near-optimal performance

Innovation

• UAV total ordering relation for data flows
• Integer linear program with Gurobi solver
• Heuristic algorithm reducing computational complexity