A Real-Time Fog Computing Approach for Healthcare Environment

In the design and development process of fog computing solutions for the Industrial Internet of Things (IIoT), we need to take into consideration the characteristics of the industrial environment that must be met. These include low latency, predictability, response time, and operating with hard real-time compiling. A starting point may be the reference fog architecture released by the OpenFog Consortium (now part of the Industrial Internet Consortium), but it has a high abstraction level and does not define how to integrate the fieldbuses and devices into the fog system. Therefore, the biggest challenges in the design and implementation of fog solutions for IIoT is the diversity of fieldbuses and devices used in the industrial field and ensuring compliance with all constraints in terms of real-time compiling, low latency, and predictability. Thus, this paper proposes a solution for a fog node that addresses these issues and integrates industrial fieldbuses. For practical implementation, there are specialized systems on chips (SoCs) that provides support for real-time communication with the fieldbuses through specialized coprocessors and peripherals. In this paper, we describe the implementation of the fog node on a system based on Xilinx Zynq UltraScale+ MPSoC ZU3EG A484 SoC.

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Goals and measures for analyzing power consumption data in manufacturing enterprises

Journal of Data, Information and Management ◽

10.1007/s42488-021-00043-5 ◽

2021 ◽

Vol 3 (1) ◽

pp. 65-82

Author(s):

Sören Henning ◽

Wilhelm Hasselbring ◽

Heinz Burmester ◽

Armin Möbius ◽

Maik Wojcieszak

Keyword(s):

Power Consumption ◽

Real Time ◽

Manufacturing Industry ◽

Fog Computing ◽

Electrical Power ◽

Time Data ◽

Manufacturing Enterprises ◽

Computing Paradigm ◽

Consumption Data ◽

Analyzing Power

AbstractThe Internet of Things adoption in the manufacturing industry allows enterprises to monitor their electrical power consumption in real time and at machine level. In this paper, we follow up on such emerging opportunities for data acquisition and show that analyzing power consumption in manufacturing enterprises can serve a variety of purposes. In two industrial pilot cases, we discuss how analyzing power consumption data can serve the goals reporting, optimization, fault detection, and predictive maintenance. Accompanied by a literature review, we propose to implement the measures real-time data processing, multi-level monitoring, temporal aggregation, correlation, anomaly detection, forecasting, visualization, and alerting in software to tackle these goals. In a pilot implementation of a power consumption analytics platform, we show how our proposed measures can be implemented with a microservice-based architecture, stream processing techniques, and the fog computing paradigm. We provide the implementations as open source as well as a public show case allowing to reproduce and extend our research.

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A Smart Collaborative Policy for Mobile Fog Computing in Rural Vitalization

Wireless Communications and Mobile Computing ◽

10.1155/2018/2643653 ◽

2018 ◽

Vol 2018 ◽

pp. 1-10 ◽

Cited By ~ 2

Author(s):

Yutong Zhou ◽

Wei Shi ◽

Fei Song

Keyword(s):

Cloud Computing ◽

Real Time ◽

Mobile Devices ◽

Policy Design ◽

Fog Computing ◽

Performance Evaluations ◽

Round Trip Time ◽

Round Trip ◽

Trip Time ◽

Smart Mobile

Mobile Fog Computing (MFC), as a crucial supplement to cloud computing, has its own special traits in many aspects. As smart mobile devices grow and vary in shapes and formats over the years, the need for real-time interactions and an easy-to-use network is imminent. In this paper, we propose a smart collaborative policy for MFC scenarios by considering the target of rural vitalization. The challenges and drawbacks of extending cloud to fog are reviewed at the beginning. Then, the analysis of policy design is presented from the perspectives of feature comparisons, urgent requirements, and possible solutions. The details of policy establishment are introduced with necessary examples. Finally, performance evaluations are provided based on simulation platforms. Validation results related to round trip time and transmission time illustrate the significant improvements of our proposal in certain ways compared to the original candidate, which enables larger deployment in impoverished areas.

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Tiarrah Computing: The Next Generation of Computing

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v8i2.pp1247-1255 ◽

2018 ◽

Vol 8 (2) ◽

pp. 1247

Author(s):

Yanish Pradhananga ◽

Pothuraju Rajarajeswari

Keyword(s):

Real Time ◽

High Performance ◽

New Technologies ◽

Fog Computing ◽

High Availability ◽

Application Development ◽

Dynamic Cluster ◽

Event Handling ◽

Application Deployment ◽

Flexible Application

The evolution of Internet of Things (IoT) brought about several challenges for the existing Hardware, Network and Application development. Some of these are handling real-time streaming and batch bigdata, real- time event handling, dynamic cluster resource allocation for computation, Wired and Wireless Network of Things etc. In order to combat these technicalities, many new technologies and strategies are being developed. Tiarrah Computing comes up with integration the concept of Cloud Computing, Fog Computing and Edge Computing. The main objectives of Tiarrah Computing are to decouple application deployment and achieve High Performance, Flexible Application Development, High Availability, Ease of Development, Ease of Maintenances etc. Tiarrah Computing focus on using the existing opensource technologies to overcome the challenges that evolve along with IoT. This paper gives you overview of the technologies and design your application as well as elaborate how to overcome most of existing challenge.

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A Layered Architecture for Fog Computing for an Effective Real Time Data Processing

International Journal of Computer Applications ◽

10.5120/ijca2018916899 ◽

2018 ◽

Vol 180 (36) ◽

pp. 23-25

Author(s):

Garima Joshi ◽

Pooja Deshpande ◽

Prasun Joshi

Keyword(s):

Data Processing ◽

Real Time ◽

Fog Computing ◽

Time Data ◽

Layered Architecture ◽

Real Time Data ◽

Real Time Data Processing

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SDTS: Security Driven Task Scheduling Algorithm for Real-Time Applications Using Fog Computing

IETE Journal of Research ◽

10.1080/03772063.2021.2010608 ◽

2021 ◽

pp. 1-20

Author(s):

Surendra Singh ◽

Sheetal Pal

Keyword(s):

Real Time ◽

Task Scheduling ◽

Scheduling Algorithm ◽

Fog Computing ◽

Task Scheduling Algorithm ◽

Real Time Applications

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Real-Time Task Scheduling in Smart Factories Employing Fog Computing

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering - Industrial IoT Technologies and Applications ◽

10.1007/978-3-030-71061-3_2 ◽

2021 ◽

pp. 18-33

Author(s):

Ming-Tuo Zhou ◽

Tian-Feng Ren ◽

Zhi-Ming Dai ◽

Xin-Yu Feng

Keyword(s):

Real Time ◽

Task Scheduling ◽

Fog Computing ◽

Time Task ◽

Smart Factories

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Fog Computing Framework for Smart City Design

International Journal of Interactive Mobile Technologies (iJIM) ◽

10.3991/ijim.v14i01.9762 ◽

2020 ◽

Vol 14 (01) ◽

pp. 109

Author(s):

Mais Haj Qasem ◽

Alaa Abu-Srhan ◽

Hutaf Natoureah ◽

Esra Alzaghoul

Keyword(s):

Cloud Computing ◽

Data Processing ◽

Real Time ◽

Smart City ◽

Network Architecture ◽

Data Exchange ◽

Fog Computing ◽

Computing Paradigm ◽

Network Usage ◽

The Cost

Fog-computing is a new network architecture and computing paradigm that uses user or near-users devices (network edge) to carry out some processing tasks. Accordingly, it extends the cloud computing with more flexibility the one found in the ubiquitous networks. A smart city based on the concept of fog-computing with flexible hierarchy is proposed in this paper. The aim of the proposed design is to overcome the limitations of the previous approaches, which depends on using various network architectures, such as cloud-computing, autonomic network architecture and ubiquitous network architecture. Accordingly, the proposed approach achieves a reduction of the latency of data processing and transmission with enabled real-time applications, distribute the processing tasks over edge devices in order to reduce the cost of data processing and allow collaborative data exchange among the applications of the smart city. The design is made up of five major layers, which can be increased or merged according to the amount of data processing and transmission in each application. The involved layers are connection layer, real-time processing layer, neighborhood linking layer, main-processing layer, data server layer. A case study of a novel smart public car parking, traveling and direction advisor is implemented using IFogSim and the results showed that reduce the delay of real-time application significantly, reduce the cost and network usage compared to the cloud-computing paradigm. Moreover, the proposed approach, although, it increases the scalability and reliability of the users’ access, it does not sacrifice much time, nor cost and network usage compared to fixed fog-computing design.

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