关键词: 无线体域网（WBAN）, 智慧医疗, 雾计算, 任务卸载

Abstract:

WBAN（Wireless Body Area Network）-based smart healthcare has attracted wide attention but faces many challenges. The traditional method introduces cloud computing to solve the resource-constraint problem of WBAN gateway device（HUB）, but its real-time performance is poor. A low-latency fog-assisted approach is proposed to process the physiological data of the WBAN, and a target node optimizing and task offloading method is designed. This method takes full account of the real-time demand of the urgent tasks and uses preemptive task scheduling and effective resource allocation to reduce the total delay of the urgent tasks. At the same time, the evaluation metrics of the target node is adjusted adaptively according to whether the task is urgent or not. When in emergency the goal is to minimize the time delay and task load, and when in non-emergency the goal is to optimize the time-latency and reliability of the target fog node for task processing. Simulation results show that the proposed method can effectively improve the real-time performance of the system and ensure the reliability of the system. Particularly, it can dramatically improve the processing delay of urgent tasks to meet the low delay processing requirements.

Key words: Wireless Body Area Network（WBAN）, smart healthcare, fog computing, task offloading