Multi-Agent Systems in Fog-Cloud Computing for Critical Healthcare Task Management Model (CHTM) Used for ECG Monitoring.

Ammar Awad Mutlag,Mazin Abed Mohammed,Mohd Khanapi Abd Ghani,Abdullah Lakhan,Begonya Garcia-Zapirain,Othman Mohd,Karrar Hameed Abdulkareem

doi:10.3390/s21206923

Abstract

In the last decade, the developments in healthcare technologies have been increasing progressively in practice. Healthcare applications such as ECG monitoring, heartbeat analysis, and blood pressure control connect with external servers in a manner called cloud computing. The emerging cloud paradigm offers different models, such as fog computing and edge computing, to enhance the performances of healthcare applications with minimum end-to-end delay in the network. However, many research challenges exist in the fog-cloud enabled network for healthcare applications. Therefore, in this paper, a Critical Healthcare Task Management (CHTM) model is proposed and implemented using an ECG dataset. We design a resource scheduling model among fog nodes at the fog level. A multi-agent system is proposed to provide the complete management of the network from the edge to the cloud. The proposed model overcomes the limitations of providing interoperability, resource sharing, scheduling, and dynamic task allocation to manage critical tasks significantly. The simulation results show that our model, in comparison with the cloud, significantly reduces the network usage by 79%, the response time by 90%, the network delay by 65%, the energy consumption by 81%, and the instance cost by 80%.

Highlights

Cloud and fog computing models have arisen in the context of the current economy and use the Internet to provide services on request for consumers [1].Both of these sectors have gained significant interest from academia and industries [2]
This paper studied the challenge of providing an efficient resource scheduling scheme for critical healthcare tasks between an edge layer, fog node layer, and cloud
We take into account a model of a multi-agent system (MAS) with four kinds of agents: personal agent (PA), master personal agent (MPA), fog node agent (FNA), and master fog node agent (MFNA)

Summary

Introduction

Cloud and fog computing models have arisen in the context of the current economy and use the Internet to provide services on request for consumers [1].Both of these sectors have gained significant interest from academia and industries [2]. A cloud extension at the network edge, may perform applications near the sources of information. Fog computing may enhance the delivery time of application services and decrease the congestion of the network [4]. On one hand, a distributed architecture in the network is not implemented in current fog computing architecture, which may lead to a node fault, and the node load is displayed [5]. The nodes of the fog are extremely heterogeneous and distributed, and most of them are reserved in terms of spatial sharing and resources. A smart collaborative balancing (SCB) scheme can be employed to dynamically adjust the orchestration of network functions and efficiently optimize the workflow patterns [9]

Methods

Results

Conclusion