# A Survey from Real-Time to Near Real-Time Applications in Fog Computing Environments
## 3 Classification of Articles
### Fog Computing Concepts
[43] propose a prediction system architecture and condition management of hydropower equipment based on the concepts of fog computing and Docker container. The goal of using the fog computing approach is to improve real-time processing capacity and address network congestion and delay issues. [PERSON] et al. [44] propose a resource provisioning scheme for partitioning a particular workload across multiple layers of computing (cloud data center, private cloud, fog nodes, and edge nodes), subject to reliability and real-time requirements. The purpose of workload partitioning is to provide design decisions, such as computing resource specification, minimum bandwidth, and the number of replicas required for each application. [PERSON] et al. [45] propose a concept of the virtual medical device deployed at the edge of the network to facilitate and provide dynamism and low latency to achieve security in Medical Cyber-Physical Systems (MCPS). In addition, a fog computing-oriented framework is proposed to enable dynamic and real-time management of physical and virtual medical devices, as well as the network that makes up MCPS. In [PERSON] and [PERSON] [46]'s paper, a three-layer framework based on IoT and fog computing for forest fire detection and real-time fire susceptibility analysis is proposed. For this, sensors are implemented to continuously monitor the environment in order to look for meteorological attributes and phenomena that cause forest fires. In addition, the fog computing layer is used to analyze in real-time the delay-sensitive data captured by the sensors. [PERSON] et al. [47] propose an application that uses the concept of fog computing for real-time facial recognition with smart glasses. Therefore, the Intelligent People Recognition Assistant (IPRA) is proposed, which aims to achieve low latency and power consumption. [PERSON] and [PERSON] [48] propose an IoT-based healthcare and fog computing framework to identify and control early-stage hypertension attacks. The system provides real-time notifications to users and doctors in case of emergency. In addition, it identifies the stage of hypertension based on the data collected by the sensors and predicts the risk level of hypertension attack on local and remote users. [PERSON] et al. [49]'s article proposes an energy-efficient fog computing-based healthcare system to monitor and maintain blood glucose levels in real-time. The J48 Graft decision tree is used to predict the level of diabetes risk with the highest classification accuracy. The goal is to monitor physiological conditions and contextual information. [PERSON] et al. [50] propose a system for continuous remote monitoring of IoT-based healthcare and fog computing. The objective of the proposed system is to improve disease analysis and diagnosis accuracy with health (blood glucose, ECG, temperature) and context (ambient temperature, humidity, and air quality) data. An encryption algorithm is applied to the system to protect the collected data. The data are then encrypted on the sensor nodes before being transmitted and decrypted on smart gateways. [PERSON] et al. [51] propose a micro-location asset tracking system using the Bluetooth Low Energy (BLE) protocol. The objective of the system is to perform real-time position estimates and asset tracking based on BLE beacons and scanners. To this end, a context-sensitive fog computing system was developed, which includes IoT controllers, sensors, and a cloud computing platform. [PERSON] and [PERSON] [52] propose a framework for integrating fog computing-based IoT control systems. The purpose of the proposed framework is to perform context-aware real-time service applicable to time-aware applications. [PERSON] [53] propose a fog node architecture that enables the IoT of devices that make up the industrial environment, integrating a set of fieldbuses such as EtherCAT, Profinet, Modbus TCP/IP, Modbus RTU, CANOpen, and Profibus. An implementation of the Distribution Service for Real-Time System (DDS) protocol is used to interconnect fog nodes.