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

TL;DR

This paper proposes a UAV-enabled computing network that enhances computing power and accessibility by adaptive UAV positioning and joint energy optimization, effectively alleviating communication bottlenecks and the island effect.

Contribution

It introduces a novel UAV-enabled computing power network framework with adaptive positioning and hybrid energy optimization, addressing complex communication and computing dynamics.

Findings

Task completion probability effectively measures UAV-CPN performance.

Joint altitude and transmit power optimization improves energy efficiency.

Significant performance gains demonstrated through extensive evaluations.

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.