Cloud-Edge Orchestration for the Internet of Things: Architecture and AI-Powered Data Processing

TLDR

The Internet of Things has penetrated critical sectors, generating massive data that demand efficient processing; limited device resources push data to cloud, but remote cloud introduces latency, so edge cloud and AI‑enhanced cloud‑edge orchestration are essential for timely IoT applications. This article surveys AI‑powered cloud‑edge orchestration architectures for IoT, reviews state‑of‑the‑art proposals, and outlines future research challenges. The authors review current AI‑driven cloud‑edge orchestration solutions, analyzing their design and performance for IoT workloads.

Abstract

The Internet of Things (IoT) has been deeply penetrated into a wide range of important and critical sectors, including smart city, water, transportation, manufacturing, and smart factory. Massive data are being acquired from a fast growing number of IoT devices. Efficient data processing is a necessity to meet diversified and stringent requirements of many emerging IoT applications. Due to the constrained computation and storage resources, IoT devices have resorted to the powerful cloud computing to process their data. However, centralized and remote cloud computing may introduce unacceptable communication delay since its physical location is far away from IoT devices. Edge cloud has been introduced to overcome this issue by moving the cloud in closer proximity to IoT devices. The orchestration and cooperation between the cloud and the edge provides a crucial computing architecture for IoT applications. Artificial intelligence (AI) is a powerful tool to enable the intelligent orchestration in this architecture. This article first introduces such a kind of computing architecture from the perspective of IoT applications. It then investigates the state-of-the-art proposals on AI-powered cloud-edge orchestration for the IoT. Finally, a list of potential research challenges and open issues is provided and discussed, which can provide useful resources for carrying out future research in this area.