Research on database pre-aggregation method for cloud-edge-device collaboration architecture

Abstract

The cloud-edge-device collaborative architecture serves as the foundation for applications such as smart manufacturing and smart cities, with collaborative computing as a critical supporting technology. Within this architecture, due to the diversity and large scale of data, traditional data management techniques struggle to support real-time querying of large-scale data. To address this, this paper proposes a database pre-aggregation method tailored to cloud-edge-device collaboration, utilizing an automated materialized view generation strategy to achieve data pre-aggregation and improve real-time query performance. Experimental results show that this pre-aggregation method reduces query time by up to 68.45%, significantly enhancing data query performance in cloud-edge-device collaborative architecture.

Keywords

• cloud-edge-device collaborative
• materialized view
• deep reinforcement learning