Hybrid Workload Enabled and Secure Healthcare Monitoring Sensing Framework in Distributed Fog-Cloud Network

Abstract

The Internet of Medical Things (IoMT) workflow applications have been rapidly growing in practice. These internet-based applications can run on the distributed healthcare sensing system, which combines mobile computing, edge computing and cloud computing. Offloading and scheduling are the required methods in the distributed network. However, a security issue exists and it is hard to run different types of tasks (e.g., security, delay-sensitive, and delay-tolerant tasks) of IoMT applications on heterogeneous computing nodes. This work proposes a new healthcare architecture for workflow applications based on heterogeneous computing nodes layers: an application layer, management layer, and resource layer. The goal is to minimize the makespan of all applications. Based on these layers, the work proposes a secure offloading-efficient task scheduling (SEOS) algorithm framework, which includes the deadline division method, task sequencing rules, homomorphic security scheme, initial scheduling, and the variable neighbourhood searching method. The performance evaluation results show that the proposed plans outperform all existing baseline approaches for healthcare applications in terms of makespan.

A Lightweight Secure Adaptive Approach for Internet-of-Medical-Things Healthcare Applications in Edge-Cloud-Based Networks

“…In [ 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 ], the authors suggested local and global searching (simulated annealing and genetic algorithm)-enabled dynamic approaches to solve the offloading and and scheduling problem in IoT networks. The main goal was to reduce local and global search times for scheduling on heterogeneous fog and cloud nodes in the system, establish a secure environment among connected nodes, and minimize attack risk in the IoT network.…”

“…On the basis of nodes, different studies suggested static and dynamic approaches based on heuristic and guided random search for combinatorial convex optimization research problems of healthcare applications in both heterogeneous and homogeneous environments. Security algorithms implemented inside these heuristics include SHA-256, MD5, CRC32 based on AES and RSA keys in the heterogeneous fog cloud nodes for healthcare applications [ 9 , 10 , 11 , 12 ].…”

Blockchain Socket Factories with RMI-Enabled Framework for Fine-Grained Healthcare Applications

“…The RPC-based blockchain presented in [ 18 , 19 , 20 , 21 , 22 , 23 , 24 ] to modify the blockchain technologies from bitcoin applications into healthcare applications. The RPC offers embedded level abstraction and allows modification inside the operating system to support healthcare applications based on blockchain technologies.…”

“…The study implemented remote procedure call services with the designed blockchain technology in the implementation part. This study implemented the existing baseline approaches, such as blockchain-offloading [ 12 , 17 , 19 , 23 , 24 ], blockchain-socket [ 9 , 11 , 14 , 16 , 20 ] and proposed blockchain socket-RPC, in the system.…”

A Real-Time Wearable Physiological Monitoring System for Home-Based Healthcare Applications

“…Other monitoring devices are limited to a single ECG or EMG channel [ 15 , 17 , 23 , 24 ] and a long-term stability test including the interference study is left out [ 15 , 17 , 18 , 24 ]. Furthermore, smart sensor networks that utilize a cloud network environment and machine learning have been proposed by various research groups [ 25 , 26 , 27 ] but existing personal healthcare monitoring devices fail to demonstrate the wearable monitoring platform with user-friendly personal smartphone connectivity features for real-time monitoring [ 18 ] and cloud networking for further data processing [ 15 , 16 , 17 , 22 , 23 , 24 ].…”