Fog Computing to Serve the Internet of Things Applications

2019 ◽  
Vol 2 (2) ◽  
pp. 44-56 ◽  
Author(s):  
Amjad Hudaib ◽  
Layla Albdour
Keyword(s):  
Internet Of Things ◽  
New Technologies ◽  
Performance Metrics ◽  
Fog Computing ◽  
High Mobility ◽  
Low Latency ◽  
Performance Measurements ◽  
Sensors And Actuators ◽  
Consumption Cost ◽  
Latency Response

Due to centralized nature for cloud computing and some other reasons, high mobility cannot be supported and low latency requirements for some applications such as Internet of Things (IoT) that require real time and mobility support. To satisfy such requirements new technologies, fog computing is a good solution, where we use edges of network for service provisioning instead of far datacenters allocated in clouds. Low latency response is the most attractive property for fog computing, which is very suitable for IoT multi-billion devices, sensors and actuators generates huge amount of data that need processing and analysis for smart decision generation. The main objective of this article is to show the super ability of fog computing over cloud-only computing. The authors present a patient monitoring system as a case study for simulation; they evaluated the performance of the system using: latency, network usage, power consumption, cost of execution and simulation execution time performance metrics. The results show that the Fog computing is superior over Cloud-only paradigm in all performance measurements.

scholarly journals Software Architecture of a Fog Computing Node for Industrial Internet of Things

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3715
Author(s):  
Ioan Ungurean ◽  
Nicoleta Cristina Gaitan
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Development Process ◽  
Fog Computing ◽  
Low Latency ◽  
Practical Implementation ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Starting Point ◽  
Hard Real Time

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.

Integrated Fog and Cloud Computing Issues and Challenges

2021 ◽  
Vol 11 (4) ◽  
pp. 174-193
Author(s):  
Shivom Sharma ◽  
Mohammad Sajid
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Fog Computing ◽  
Low Latency ◽  
Traffic Lights ◽  
Computing Paradigm ◽  
Iot Devices ◽  
Smart Traffic ◽  
Smart Computing ◽  
Cloud Resources

Due to the exponential growth in the number of internet-of-things (IoT) devices like smartphones and smart traffic lights, the data generated by the devices and the service requirements are increasing. The biggest issue in accessing the cloud computing is that all processing is done on cloud resources. For cloud-based services, it is utmost required to send all data to cloud resources which leads to many issues and challenges. The important issues are large volume of data, low latency rate, low bandwidth. In order to resolve such issues, there is an essential need of a smart computing paradigm which works as a moderator between cloud computing and IoT devices to improve the performances of the services, maximizing utilization of computing resources, storage. This work presents an overview and description of fog computing in the context of cloud computing and internet of things (IoT) and also sheds light on the key differences between cloud computing and fog computing. This work also presents various issues and challenges in the context of fog computing with its various applications.

Fog Computing and Its Role in the Internet of Things

2019 ◽  
pp. 63-71 ◽  
Author(s):  
Nisha Angeline C. V. ◽  
Raja Lavanya
Keyword(s):  
Internet Of Things ◽  
Wireless Sensors ◽  
Smart Cities ◽  
Fog Computing ◽  
Connected Vehicle ◽  
Location Awareness ◽  
Sensors And Actuators ◽  
Computing Paradigm ◽  
The Internet Of Things

Fog computing extends the cloud computing paradigm to the edge of the network, thus enabling a new breed of applications and services. Defining characteristics of the Fog are 1) low latency and location awareness, 2) widespread geographical distribution, 3) mobility, 4) very large number of nodes, 5) predominant role of wireless access, 6) strong presence of streaming and real time applications, and 7) heterogeneity. In this chapter, the authors argue that the above characteristics make the Fog the appropriate platform for a number of critical internet of things (IoT) services and applications, namely connected vehicle, smart grid, smart cities, and in general, wireless sensors and actuators networks (WSANs).

scholarly journals How to Enable Delay Tolerant Network Solutions for Internet of Things: From Taxonomy to Open Challenges

Proceedings ◽  
2019 ◽  
Vol 31 (1) ◽  
pp. 24
Author(s):  
Selma Bounsiar ◽  
Fatima Zohra Benhamida ◽  
Abderrazak Henni ◽  
Diego López de Ipiña ◽  
Diego Casado Mansilla
Keyword(s):  
Internet Of Things ◽  
Routing Protocols ◽  
New Technologies ◽  
Fog Computing ◽  
Delay Tolerant Network ◽  
Dtn Routing ◽  
Communication Challenges ◽  
Delay Tolerant ◽  
Open Issues

Internet of Things (IoT) is witnessing an increasing range of application domains (industry 4.0, eHealth, smart city, etc.). Meanwhile, IoT is still facing communication challenges because of limited capabilities in computing, storage and energy constraints of smart objects. The use of Delay Tolerant Network (DTN) as basis for communication in IoT is promising but needs more development. In this paper, we present a literature review and a classification of DTN routing protocols. Furthermore, we survey a number of DTN solutions for IoT and propose a new taxonomy to motivate the importance of enabling DTN for IoT applications. The novelty of this classification is the focus on X-DTN category, which combines Delay Tolerant schemes with new technologies (e.g., Fog Computing). We also point out some open issues for potential Delay Tolerant IoT schemes.

scholarly journals Energy Efficient Decision based Routing Technique using Fog Computing Paradigm

2019 ◽  
Vol 8 (9S) ◽  
pp. 964-969
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Energy Efficient ◽  
New Technologies ◽  
Fog Computing ◽  
Emergency Situation ◽  
The Internet ◽  
Computing Paradigm ◽  
Current Scenario ◽  
The Internet Of Things

In the era of new technologies, Fog computing becomes very popular in today’s scenario. Fog computing paradigm brings a concept that extends cloud computing to the edge and close proximity to the Internet of Things (IoT) network. The fundamental components of fog computing are fog nodes. Additionally, fog nodes are energy efficient nodes. Numerous fog nodes are deployed in the associated fields that will handle the Internet of Things (IoT) sensors computation. Meanwhile, the Internet of Things (IoT) faces challenges, among which energy efficiency is one of the most prominent or critical challenges in the current scenario. However, sensor devices are an energy constraintthatcreateshotspotduringtheroutingprocess.Forthis reason,tohandlesuchconstraints,thispaperpresentsaneffective hotspot mechanism using fog nodes that demonstrate the routing process and directed the sensors to choose the routing path as selected by the fog node. Moreover, fog node will act as a decision maker node and maintain the energy efficiency of sensors during the routing as fog nodes are energy efficient nodes. As it moves towards the emergency situation, the most appropriate and effective routing approach has been designed who maintain the energy level of sensors will be high during the routing process. The proposed routing technique could be better performance for the sake of efficient routing in terms of energy consumption and prolonging networklifetime.

scholarly journals AN EFFICIENT FOG ENABLED HEALTHCARE MAINTENANCE SYSTEM USING INTERNET OF THINGS WITH DEEP LEARNING STRATEGIES

2021 ◽  
Vol 9 (1) ◽  
pp. 659-665
Author(s):  
G. S. Gunanidhi, R. Krishnaveni
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Internet Of Things ◽  
Learning Strategies ◽  
New Technologies ◽  
Learning Strategy ◽  
Fog Computing ◽  
Health Records ◽  
Maintenance System ◽  
High Efficient

Internet of Things (IoT) is the ruling term now-a-days, in which it attracts several smart gadgets and application due to its robust nature and support. In healthcare industry several new technologies are required to improve the stability and provide transparent services to clients. The integration of healthcare maintenance system with respect to Internet of Things support leads to a drastic change in healthcare field as well as this provision provides huge advantages to users. This paper is intended to provide an intense healthcare maintenance scheme by using latest technologies such as Deep Learning, Internet of Things, Fog Computing and Artificial Intelligence. All these innovations are associated together to build a new deep learning strategy called Intense Health Analyzing Scheme (IHAS), in which this proposed approach provides all provisions to clients such as Doctors and Patients with respect to monitor the patient details from anywhere at anytime without any range boundaries. The Fog Computing is an innovative domain, in which it provides ability to the server to operate based on hurdle free processing logic. Artificial Intelligence logic is used to manipulate the health data based on previously trained health records, so that the predictions are more fine compare to the classical healthcare schemes. In traditional schemes it is difficult to raise an alert based on the emergency situation predictions, but in the proposed deep learning strategy assists the proposed approach to send an alert instantly if any emergency cases occurred on patient end. Generally the Fog Servers are used to reduce the occupancy of the storage server and provide reliable storage abilities to server, but in this proposed approach, the fog server is utilized for priority wise data handling nature and stores the health records accordingly. In this nature, the fog servers are handled and provide high efficient results to the clients in an innovative way. With the help of deep learning procedures, the health records are clearly prioritized and maintained into the server end for monitoring. For all this paper introduced a new logic of healthcare maintenance scheme IHAS to provide efficient support to patients as well as doctors in clear manner.

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