Dew-based offline computing architecture for healthcare IoT

Abstract

Due to the resource-constraint nature and lack of lightweight computing solutions for diagnostic devices in healthcare IoT, provisioning time-critical responses is still challenging. In this paper, we propose DC-Health, a Dew Computing enabled IoT healthcare solution for offline and ultra-low latency decisions. The proposed solution connects a large number of healthcare devices and provisions user-specific services even when Internet connectivity is not available. The computation module is placed at the extreme edge rather than the cloud to reduce the complexity and to improve the user-specific services. In addition to the other computing facilities provided by the cloud, fog, and edge, our solution performs with a negligible dependency on the Internet. We develop a prototype of DC-Health, which monitors the heart condition using the ECG sensors with end-mile services, flexibility in terms of user-control, and mobility feature. The experimental implementations show that the proposed architecture minimizes the network response time by at least 92% and 98%, compared to the fog and cloud-based approaches, respectively. Along with this, the proposed technique also reduces the CPU and memory usages, and response time by around 30% compared to the conventional method.

Keywords

• Healthcare IoT
• Dew Computing
• Edge computing
• Time-critical applications