Edge Intelligence Computing Power Collaboration Framework for Connected Health
Boran Yang, Yong Wang, Yan He · 2023
Connected health is a rapidly advancing field that encompasses wireless, digital, mobile, and telehealth technologies. It aims to improve healthcare management by leveraging abundant health data shared by individuals for proactive and efficient care. Edge intelligence (EI), which integrates artificial intelligence (AI) with edge computing, has emerged as a transformative approach to connected health. This paper proposes an EI computing power collaboration framework for connected health. The framework leverages the computing power of edge devices, including consumer electronics, to enhance connected health services. In addition, the framework incorporates edge caching and blockchain technology for efficient healthcare data storage and secure EI computing power collaborations. Deep reinforcement learning, specifically the MuZero algorithm, is used to generate optimal strategies for adjusting the supply-demand relationship of EI computing power. The proposed framework enables responsive and economic healthcare services and empowers various compute-intensive connected health applications.