Fuzzy-based Fog Computing for Real-Time Data Transmission in Healthcare Internet-of-Things

Abstract

The increase in the growth of healthcare IoT devices leads to a large volume and variety of healthcare data. The large healthcare data generates high data traffic that will cause network bottleneck and burdens the cloud with an extra amount of workload. The main requirement of healthcare IoT is to have a minimum network and service latency along with conserve network bandwidth. Both the volume of data as well as factors related to internet connectivity may lead to high network latency in analyzing and acting upon device data. Therefore, due to high network latency, high service latency and large data transmission from IoT devices, the cloud is unable to send the patient health data in real-time mode. Fog computing is a new approach to address this requirement of cloud and healthcare IoT devices. A tentative novel solution for the above-mentioned problem using fuzzy-based fog computing architecture that integrates healthcare IoT devices with the cloud and uses fog services with Fuzzy Data Packet Allocation (FDPA) algorithm. Using virtualization and fuzzy inference system (FIS) in fog computing, the proposed algorithm is expected to transfer the patient health data in real-time mode to agencies and doctors.