Offloading decision and resource allocation in aerial computing: A comprehensive survey

Abstract

Aerial computing can facilitate the successful execution of tasks, ensuring low latency for Internet of things (IoT) devices. It gains greater significance and practicality by offering both edge and cloud computing services for IoT applications. However, in aerial computing, resources such as computing power, energy, and bandwidth are limited and constrained. Consequently, certain tasks must be offloaded to different platforms for sustained operation. Hence, the offloading decision (OD) and resource allocation (RA) are closely interconnected. Currently, numerous research efforts are underway to address efficient offloading and resource management. However, a comprehensive review of OD and RA in aerial computing platforms is yet to be explored. This study presents a thorough survey of OD and RA in aerial computing platforms, extensively reviewing and comparatively discussing various algorithms and approaches. The discussion delves deep into key design issues and also explores unresolved challenges, providing possible future directions. Our work can help researchers in studying and designing efficient methods for task offloading and resource management across different application scenarios.