Toward a Heterogeneous Mist, Fog, and Cloud-Based Framework for the Internet of Healthcare Things

Abstract

Rapid developments in the fields of information and communication technology and microelectronics allowed seamless interconnection among various devices letting them to communicate with each other. This technological integration opened up new possibilities in many disciplines including healthcare and well-being. With the aim of reducing healthcare costs and providing improved and reliable services, several healthcare frameworks based on Internet of Healthcare Things (IoHT) have been developed. However, due to the critical and heterogeneous nature of healthcare data, maintaining high quality of service (QoS) -in terms of faster responsiveness and data-specific complex analytics -has always been the main challenge in designing such systems. Addressing these issues, this paper proposes a five-layered heterogeneous mist, fog, and cloud based IoHT framework capable of efficiently handling and routing (near-)real-time as well as offline/batch mode data. Also, by employing software defined networking and link adaptation based load balancing, the framework ensures optimal resource allocation and efficient resource utilization. The results, obtained by simulating the framework, indicate that the designed network via its various components can achieve high QoS, with reduced end-to-end latency and packet drop rate, which is essential for developing next generation e-healthcare systems.

Architecting and Deploying IoT Smart Applications: A Performance–Oriented Approach

“…In other words, we advocate that IoT architectures must have an active role in the deployment of new applications. An option is to embed deployment locations within the architecture, explicitly recognizing the existence of edge processing [21]. However, we consider that a new concept is needed to separate the concerns of layered software components from staged deployment locations.…”

“…While the fog aims at reducing bandwidth usage, latency, and data communication with the datacenter, mist computing extends this concept further in IoT-based systems, closer to the sensors and actuators [12]. Although there is no consensus about the definition of mist, some common understanding can be found, such as being located closer to the devices [21,41]. Mist can be considered the lowest level of a hierarchical fog computing system.…”

“…Since smart applications will typically have to deal with thousands of devices-or considerably more-performance and scalability concerns are key to any successful IoT deployment. Yet, most current reported experiences show: (a) small-scale pilots [7,44]; (b) simulation-based or analytical results [21,45]; (c) measurement-based results with limited scope [19,46]; (d) no quantitative results at all [2,3,5,8,9,11,12,16,24,37,47]. Also, different architectural and deployment choices for IoT systems affect scalability, and real-time decision-making is possible in an environment composed of thousands of sensors [4,48].…”

“…By representing architecture layers and deployment stages separately and mapping one into the other, we obtain a flexible mechanism for reasoning on functionality and placement and being able to provide deployment views to IoT smart applications on different scenarios. We consider it a more robust approach compared to mixing both concerns in a single architecture, such as the one proposed by Asif-Ur-Rahman et al for smart healthcare applications [21].…”

Edge Intelligence: The Confluence of Edge Computing and Artificial Intelligence

“…5G brings enhanced mobile broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC) and massive Machine Type Communications (mMTC). With the proliferation of the Internet of Things (IoTs), more and more data is created by widespread and geographically distributed mobile and IoT devices, instead of the mega-scale cloud datacenters [1]. Specifically, according to the prediction of Ericsson, 45% of the 40ZB global internet data will be generated by IoT devices in 2024 [2].…”