scholarly journals FOG computing and its various uses in different applications

2018 ◽  
Vol 7 (2.7) ◽  
pp. 345
Author(s):  
Chandra Sekhar Maganty ◽  
Kothamasu Kiran Kumar
Keyword(s):  
Cloud Computing ◽  
High Speed ◽  
Fog Computing ◽  
End User ◽  
New Era ◽  
Streaming Applications ◽  
Computing Model ◽  
Use Of Resources ◽  
To Come ◽  
Edge And Fog Computing

Cloud computing is the transformation, which involves storing large applications where data or information is exchanged among differ-ent platforms for giving good service to clients who belong to different organizations. It assures great use of resources by making data, software and infrastructure available with minimal cost along with security and reliability. Even though cloud computing gives many advantages, it has certain limitations like network congestion, fault tolerance, less bandwidth etc. To come out of this issue a new era computing model is introduced called Fog Computing. This new computing model can transfer fragile data without any delay to other devices in the network. The only difference between both is fog is located more close to the end user or the device and gives response to the client instantly. Moreover, it is beneficial to the real time streaming applications, internet of things which need reliable internet con-nectivity along with high speed. This paper is a review on Fog Computing, differences in edge and fog computing, use cases of fog and the architecture.

Security Challenges in Fog Computing

2019 ◽  
pp. 148-164
Author(s):  
Anshu Devi ◽  
Ramesh Kait ◽  
Virender Ranga
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Cloud Security ◽  
Trust Model ◽  
Security Threats ◽  
New Paradigm ◽  
Computing Model ◽  
Security Challenges ◽  
Security Concerns ◽  
Distinct Features

Fog computing is a term coined by networking giant Cisco. It is a new paradigm that extends the cloud computing model by conferring computation, storage, and application services at the periphery of networks. Fog computing is a gifted paradigm of cloud computing that facilitates the mobility, portability, heterogeneity, and processing of voluminous data. These distinct features of fog help to reduce latency and make it suitable for location-sensitive applications. Fog computing features raise new security concerns and challenges. The existing cloud security has not been implemented directly due to mobility, heterogeneity of fog nodes. As we know, IoT has to process large amount of data quickly; therefore, it has various functionality-driven applications that escalate security concerns. The primary aim of this chapter is to present the most recent security aspects such as authentication and trust, reputation-based trust model, rogue fog node and authentication at different level, security threats, challenges, and also highlights the future aspects of fog.

Vehicular Cloud and Fog Computing Architecture, Applications, Services, and Challenges

2020 ◽  
pp. 268-296
Author(s):  
Priyanka Gaba ◽  
Ram Shringar Raw
Keyword(s):  
Cloud Computing ◽  
High Speed ◽  
Fog Computing ◽  
Detailed Comparison ◽  
Fast Response ◽  
Computing Technique ◽  
Vehicular Cloud ◽  
Network Bandwidth ◽  
Real Time Applications ◽  
Safety Features

VANET, a type of MANET, connects vehicles to provide safety and non-safety features to the drivers and passengers by exchanging valuable data. As vehicles on road are increasing to handle such data cloud computing, functionality is merged with vehicles known as Vehicular Cloud Computing(VCC) to serve VANET with computation, storage, and networking functionalities. But Cloud, a centralized server, does not fit well for vehicles needing high-speed processing, low latency, and more security. To overcome these limitations of Cloud, Fog computing was evolved, extending the functionality of cloud computing model to the edge of the network. This works well for real time applications that need fast response, saves network bandwidth, and is a reliable, secure solution. An application of Fog is with vehicles known as Vehicular Fog Computing (VFC). This chapter discusses cloud computing technique and its benefits and drawbacks, detailed comparison between VCC and VFC, applications of Fog Computing, its security, and forensic challenges.

Novel Taxonomy to Select Fog Products and Challenges Faced in Fog Environments

2021 ◽  
pp. 2558-2571
Author(s):  
Akashdeep Bhardwaj
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
High Speed ◽  
Low Cost ◽  
Fog Computing ◽  
Research Work ◽  
Cloud Services ◽  
Smart Devices ◽  
Viable Solution ◽  
Last Mile

This article describes how the rise of fog computing to improve cloud computing performance and the acceptance of smart devices is slowly but surely changing our future and shaping the computing environment around us. IoT integrated with advances in low cost computing, storage and power, along with high speed networks and big data, supports distributed computing. However, much like cloud computing, which are under constant security attacks and issues, distributed computing also faces similar challenges and security threats. This can be mitigated to a great extent using fog computing, which extends the limits of Cloud services to the last mile edge near to the nodes and networks, thereby increasing the performance and security levels. Fog computing also helps increase the reach and comes across as a viable solution for distributed computing. This article presents a review of the academic literature research work on the Fog Computing. The authors discuss the challenges in Fog environment and propose a new taxonomy.

scholarly journals An IoT-Based Fog Computing Model

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2783 ◽  
Author(s):  
Kun Ma ◽  
Antoine Bagula ◽  
Clement Nyirenda ◽  
Olasupo Ajayi
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Physical Distance ◽  
Cloud Services ◽  
Daily Lives ◽  
Service Computing ◽  
Network Bandwidth ◽  
Computing Model ◽  
Data Source ◽  
The Internet Of Things

The internet of things (IoT) and cloud computing are two technologies which have recently changed both the academia and industry and impacted our daily lives in different ways. However, despite their impact, both technologies have their shortcomings. Though being cheap and convenient, cloud services consume a huge amount of network bandwidth. Furthermore, the physical distance between data source(s) and the data centre makes delays a frequent problem in cloud computing infrastructures. Fog computing has been proposed as a distributed service computing model that provides a solution to these limitations. It is based on a para-virtualized architecture that fully utilizes the computing functions of terminal devices and the advantages of local proximity processing. This paper proposes a multi-layer IoT-based fog computing model called IoT-FCM, which uses a genetic algorithm for resource allocation between the terminal layer and fog layer and a multi-sink version of the least interference beaconing protocol (LIBP) called least interference multi-sink protocol (LIMP) to enhance the fault-tolerance/robustness and reduce energy consumption of a terminal layer. Simulation results show that compared to the popular max–min and fog-oriented max–min, IoT-FCM performs better by reducing the distance between terminals and fog nodes by at least 38% and reducing energy consumed by an average of 150 KWh while being at par with the other algorithms in terms of delay for high number of tasks.

Novel Taxonomy to Select Fog Products and Challenges Faced in Fog Environments

2018 ◽  
Vol 1 (1) ◽  
pp. 35-49 ◽  
Author(s):  
Akashdeep Bhardwaj
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
High Speed ◽  
Low Cost ◽  
Fog Computing ◽  
Research Work ◽  
Cloud Services ◽  
Smart Devices ◽  
Viable Solution ◽  
Last Mile

This article describes how the rise of fog computing to improve cloud computing performance and the acceptance of smart devices is slowly but surely changing our future and shaping the computing environment around us. IoT integrated with advances in low cost computing, storage and power, along with high speed networks and big data, supports distributed computing. However, much like cloud computing, which are under constant security attacks and issues, distributed computing also faces similar challenges and security threats. This can be mitigated to a great extent using fog computing, which extends the limits of Cloud services to the last mile edge near to the nodes and networks, thereby increasing the performance and security levels. Fog computing also helps increase the reach and comes across as a viable solution for distributed computing. This article presents a review of the academic literature research work on the Fog Computing. The authors discuss the challenges in Fog environment and propose a new taxonomy.

scholarly journals Reliablity in the Fog Computing

10.29007/nc47 ◽  
2018 ◽  
Author(s):  
Manu Sharma
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Fog Computing ◽  
Cloud Environment ◽  
End User ◽  
Computing Technology ◽  
Digital Innovation ◽  
Security Issues ◽  
Remote Server ◽  
The World

In the world of Digital Innovation “Cloud Computing” is not just a word or a technology but a paramount to the organizations now days. Because it is not easy to store, compute the data on an internet and central remote server to manage a huge bulk of data and information. It is well known that cloud computing provides data, storage of data, computation of data to the end user also by providing the services to the end users by the different applications. So, now the Fog Computing Is generally a concept to extend the cloud computing technology as it also does the same function which cloud computing functionality as well. It is not the replacement but the enhanced version of cloud which provides a security on the cloud environment by isolating user’s data which is saved on the Edge Devices. Fog Computing enables a user to save their data to nearby devices. In this paper the security issues also the technology which is used for security in this enhanced concept of cloud is mentioned.

Fog Computing and Networking Architectures

2019 ◽  
pp. 53-67
Author(s):  
Minal Moharir ◽  
Bharat Rahuldhev Patil
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Airport Security ◽  
Low Latency ◽  
Use Case ◽  
Effective Solution ◽  
End User ◽  
Primary Motivation ◽  
Networking Architectures ◽  
Fog Network

The demerits of cloud computing lie in the velocity, bandwidth, and privacy of data. This chapter focuses on why fog computing presents an effective solution to cloud computing. It first explains the primary motivation behind the use of fog computing. Fog computing, in essence, extends the services of the cloud towards the edge of the network (i.e., towards the devices nearer to the customer or the end user). Doing so offers several advantages. Some of the discussed advantages are scalability, low latency, reducing network traffic, and increasing efficiency. The chapter then explains the architecture to implement a fog network, followed by its applications. Some commercial fog products are also discussed, and a use case for an airport security system is presented.

scholarly journals Ultra-Reliable and Low-Latency Computing in the Edge with Kubernetes

2021 ◽  
Vol 19 (3) ◽  
Author(s):  
László Toka
Keyword(s):  
High Reliability ◽  
Fog Computing ◽  
Resource Provisioning ◽  
Use Case ◽  
End User ◽  
Delay Constraints ◽  
Edge And Fog Computing ◽  
Novel Applications ◽  
Stream Analytics ◽  
Potential Use

AbstractNovel applications will require extending traditional cloud computing infrastructure with compute resources deployed close to the end user. Edge and fog computing tightly integrated with carrier networks can fulfill this demand. The emphasis is on integration: the rigorous delay constraints, ensuring reliability on the distributed, remote compute nodes, and the sheer scale of the system altogether call for a powerful resource provisioning platform that offers the applications the best of the underlying infrastructure. We therefore propose Kubernetes-edge-scheduler that provides high reliability for applications in the edge, while provisioning less than 10% of resources for this purpose, and at the same time, it guarantees compliance with the latency requirements that end users expect. We present a novel topology clustering method that considers application latency requirements, and enables scheduling applications even on a worldwide scale of edge clusters. We demonstrate that in a potential use case, a distributed stream analytics application, our orchestration system can reduce the job completion time to 40% of the baseline provided by the default Kubernetes scheduler.

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