Edge-Cloud Cooperative Intelligence for Computation Offloading in Connected Living

In the context of the interconnected living environment, an extensive volume of data is continually generated by Internet of Things (IoT) devices, which requires proficient storage, real-time processing, and analysis. Efficient data processing and management play a pivotal role in healthcare for monitoring and detecting abnormal health conditions, especially in the era of the COVID-19 pandemic. Computing paradigms such as cloud intelligence and edge intelligence are considered to be efficient in achieving such goals. Owing to their own shortcomings (e.g., long latency for cloud intelligence and insufficient computing capability for edge intelligence), we propose an efficient edge-cloud cooperative intelligence (EC2I) for data processing and task offloading. Particularly, we try to harness the computing capability of high-end IoT devices and treat them as edge devices. We aim to address the central question of how and where computational tasks are executed within the realm of connected living. Furthermore, we delve into several opportunities and challenges, thereby shedding light on potential avenues for future research in this domain.