UAV-enabled Computing Power Networks: Design and Performance Analysis under Energy Constraints

2026-01-14

IEEE Transactions on Mobile Computing

AI Summary

This work addresses the communication bottlenecks and computational resource fragmentation in multi-access edge computing by proposing a UAV-enabled computing power network (UAV-CPN). In this framework, unmanned aerial vehicles (UAVs) are dynamically deployed as relays to offload computational tasks from request zones to heterogeneous computing nodes comprising vehicular units and edge servers. Under hybrid energy constraints combining fuel cells and batteries, the scheme jointly optimizes UAV flight altitude and transmission power, while introducing a task completion probability metric to quantify system performance. Experimental results demonstrate that the proposed approach significantly improves task completion rates by effectively co-optimizing communication and computing resources, thereby substantially enhancing the network’s computing service capability under limited energy budgets.

Technology Category

• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Machine Learning: Learning on the Edge & Model Compression

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

This paper presents an innovative framework that boosts computing power by utilizing ubiquitous computing power distribution and enabling higher computing node accessibility via adaptive UAV positioning, establishing a UAV-enabled Computing Power Network (UAV-CPN). In a UAV-CPN, a UAV functions as a dynamic relay, outsourcing computing tasks from the request zone to an expanded service zone with diverse computing nodes, including vehicle onboard units, edge servers, and dedicated powerful nodes. This approach has the potential to alleviate communication bottlenecks and overcome the"island effect"observed in multi-access edge computing. A significant challenge is to quantify computing power performance under complex dynamics of communication and computing. To address this challenge, we introduce task completion probability to capture the capability of UAV-CPNs for task computing. We further enhance UAV-CPN performance under a hybrid energy architecture by jointly optimizing UAV altitude and transmit power, where fuel cells and batteries collectively power both UAV propulsion and communication systems. Extensive evaluations show significant performance gains, highlighting the importance of balancing communication and computing capabilities, especially under dual-energy constraints. These findings underscore the potential of UAV-CPNs to significantly boost computing power.

Problem

• UAV-enabled Computing Power Network
• energy constraints
• communication bottleneck
• island effect
• computing power performance

Innovation

• UAV-enabled Computing Power Network
• adaptive UAV positioning
• task completion probability
• hybrid energy architecture
• computing-communication co-optimization