Supporting UAVs with Edge Computing: A Review of Opportunities and Challenges

TL;DR

This paper reviews how integrating edge computing with UAVs enhances their performance by reducing latency, improving energy efficiency, and supporting complex tasks, addressing limitations posed by UAVs' battery constraints.

Contribution

It provides a comprehensive systematic review of current research on UAVs supported by edge computing, highlighting key opportunities and challenges in this emerging field.

Findings

Edge computing reduces UAV task latency.

Support for energy-efficient UAV operations.

Improved reliability in UAV applications.

Abstract

Over the last years, Unmanned Aerial Vehicles (UAVs) have seen significant advancements in sensor capabilities and computational abilities, allowing for efficient autonomous navigation and visual tracking applications. However, the demand for computationally complex tasks has increased faster than advances in battery technology. This opens up possibilities for improvements using edge computing. In edge computing, edge servers can achieve lower latency responses compared to traditional cloud servers through strategic geographic deployments. Furthermore, these servers can maintain superior computational performance compared to UAVs, as they are not limited by battery constraints. Combining these technologies by aiding UAVs with edge servers, research finds measurable improvements in task completion speed, energy efficiency, and reliability across multiple applications and industries. This systematic literature review aims to analyze the current state of research and collect, select, and extract the key areas where UAV activities can be supported and improved through edge computing.