scholarly journals Advanced Technique for Efficiently and Securely Accessing data in the Fog and Cloud Network

2021 ◽  
pp. 573-578
Author(s):  
Dhanashri M. Kale ◽  
Dr. Vilas M. Thakare
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Fog Computing ◽  
Future Research ◽  
Advanced Technique ◽  
Computing Architecture ◽  
Use Of Technology ◽  
Radio Access ◽  
Architecture Evaluation ◽  
Cloud Network

With the increased use of technology , the fog computing network is being used on a large scale The integration of fog computing into cloud computing network is full of advantages and increases features. The network currently is secured but also subjected to various challenges. In this paper, we have reviewed five different schemes which are : Architecture Harmonization Between Cloud Radio Access Networks and Fog Networks, Fog Computing Architecture, Evaluation, and Future Research Directions, Indie Fog: An Efficient Fog-Computing Infrastructure for the Internet of Things, A Framework of Fog Computing: Architecture, Challenges, and Optimization, A Critical Analysis on Integration of Fog Computing and Cloud Computing. These schemes discussed here provide certain features but there are some limitations in it. So we propose a new scheme that helps to overcome the challenges of these previous schemes.

scholarly journals Fog Computing in the context of Smart Home, voice assistant and the future of IoT

2020 ◽  
Vol 21 (1) ◽  
pp. 6-12
Author(s):  
Javier Pinzón Castellanos ◽  
Miguel Antonio Cadena Carter
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
Data Transmission ◽  
Smart Home ◽  
Fog Computing ◽  
Relevant Information ◽  
Raspberry Pi ◽  
Thermal Sensors ◽  
Computing Architecture ◽  
The Future

Fog Computing is the distributed computing layer that lies between the user and the cloud. A successful fog architecture reduces delay or latency and increases efficiency. This paper describes the development and implementation of a distributed computing architecture applied to an automation environment that uses Fog Computing as an intermediary with the cloud computing layer. This study used a Raspberry Pi V3 board connected to end control elements such as servomotors and relays, indicators and thermal sensors. All is controlled by an automation framework that receives orders from Siri and executes them through predetermined instructions. The cloud connection benefits from a reduced amount of data transmission, because it only receives relevant information for analysis.

scholarly journals Towards Distributed Data Management in Fog Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Vasileios Moysiadis ◽  
Panagiotis Sarigiannidis ◽  
Ioannis Moscholios
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Large Scale ◽  
Fog Computing ◽  
Cloud Services ◽  
Smart Devices ◽  
Distributed Data ◽  
Storage Allocation ◽  
Huge Amount ◽  
Distributed Data Storage

In the emerging area of the Internet of Things (IoT), the exponential growth of the number of smart devices leads to a growing need for efficient data storage mechanisms. Cloud Computing was an efficient solution so far to store and manipulate such huge amount of data. However, in the next years it is expected that Cloud Computing will be unable to handle the huge amount of the IoT devices efficiently due to bandwidth limitations. An arising technology which promises to overwhelm many drawbacks in large-scale networks in IoT is Fog Computing. Fog Computing provides high-quality Cloud services in the physical proximity of mobile users. Computational power and storage capacity could be offered from the Fog, with low latency and high bandwidth. This survey discusses the main features of Fog Computing, introduces representative simulators and tools, highlights the benefits of Fog Computing in line with the applications of large-scale IoT networks, and identifies various aspects of issues we may encounter when designing and implementing social IoT systems in the context of the Fog Computing paradigm. The rationale behind this work lies in the data storage discussion which is performed by taking into account the importance of storage capabilities in modern Fog Computing systems. In addition, we provide a comprehensive comparison among previously developed distributed data storage systems which consist of a promising solution for data storage allocation in Fog Computing.

From Cloud Computing to Fog Computing

2018 ◽  
Vol 1 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Sanjay P. Ahuja ◽  
Niharika Deval
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Cost Savings ◽  
End Users ◽  
Internet Technology ◽  
Future Research ◽  
Computing Paradigm ◽  
Close Proximity ◽  
Iot Devices ◽  
Communication Control

This article describes how in recent years, Cloud Computing has emerged as a fundamental computing paradigm that has significantly changed the approach of enterprises as well as end users towards implementation of Internet technology. The key characteristics such as on-demand resource provision, scalability, rapid elasticity, higher flexibility, and significant cost savings have influenced enterprises of all sizes in the wide and successful adoption of Cloud Computing. Despite numerous advantages, Cloud Computing has its fair share of downsides as well. One of those major concerns is latency issues which has relevance to the Internet of Things (IoT). A new computing paradigm has been proposed by Cisco in early 2014 and termed 'Fog Computing'. Fog Computing otherwise known as Edge Computing is the integration of Cloud Computing and IoT. Being located in close proximity to the IoT devices, the Fog assists with latency requirements of IoT related applications. It also meets the data processing needs of IoT devices which are resource constrained by bringing computation, communication, control and storage closer to the end users. Clouds continue to offer support for data analytics. One can think of the IoT-Fog-Cloud as being part of a continuum. This article surveys the current literature on Fog Computing and provides a discussion on the background, details and architecture of Fog Computing, as well as the application areas of Fog Computing. The article concludes with some recommendations in the areas of future research.

Vehicular Fog Computing

2017 ◽  
Vol 1 (2) ◽  
pp. 15-23 ◽  
Author(s):  
Varun G. Menon ◽  
Joe Prathap
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Fog Computing ◽  
Security And Privacy ◽  
Future Research ◽  
Collision Warning ◽  
Efficient Resource ◽  
Hoc Networks

In recent years Vehicular Ad Hoc Networks (VANETs) have received increased attention due to its numerous applications in cooperative collision warning and traffic alert broadcasting. VANETs have been depending on cloud computing for networking, computing and data storage services. Emergence of advanced vehicular applications has led to the increased demand for powerful communication and computation facilities with low latency. With cloud computing unable to satisfy these demands, the focus has shifted to bring computation and communication facilities nearer to the vehicles, leading to the emergence of Vehicular Fog Computing (VFC). VFC installs highly virtualized computing and storage facilities at the proximity of these vehicles. The integration of fog computing into VANETs comes with a number of challenges that range from improved quality of service, security and privacy of data to efficient resource management. This paper presents an overview of this promising technology and discusses the issues and challenges in its implementation with future research directions.

Fog Computing Architecture for Indoor Disaster Management

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Asep Id Hadiana ◽  
Keyword(s):  
Cloud Computing ◽  
Disaster Management ◽  
Network Traffic ◽  
Fog Computing ◽  
Building Structures ◽  
Quick Response ◽  
Computing Architecture ◽  
Iot Applications ◽  
Management Architecture

Most people spend their time indoors. Indoors have a higher complexity than outdoors. Moreover, today's building structures are increasingly sophisticated and complex, which can create problems when a disaster occurs in the room. Fire is one of the disasters that often occurs in a building. For that, we need disaster management that can minimize the risk of casualties. Disaster management with cloud computing has been extensively investigated in other studies. Traditional ways of centralizing data in the cloud are almost scalable as they cannot cater to many latency-critical IoT applications, and this results in too high network traffic when the number of objects and services increased. It will be especially problematic when in a disaster that requires a quick response. The Fog infrastructure is the beginning of the answer to such problems. This research started with an analysis of literature and hot topics related to fog computing and indoor disasters, which later became the basis for creating a fog computing-based architecture for indoor disasters. In this research, fog computing is used as the backbone in disaster management architecture in buildings. MQTT is used as a messaging protocol with the advantages of simplicity and speed. This research proposes a disaster architecture for indoor disasters, mainly fire disasters

Cloud Computing for BioLabs

2015 ◽  
pp. 1272-1293
Author(s):  
Abraham Pouliakis ◽  
Aris Spathis ◽  
Christine Kottaridi ◽  
Antonia Mourtzikou ◽  
Marilena Stamouli ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Analysis ◽  
Drug Design ◽  
Large Scale ◽  
Future Research ◽  
New Paradigm ◽  
Computing Power ◽  
The Everyday ◽  
Potential Applications ◽  
Computational Resources

Cloud computing has quickly emerged as an exciting new paradigm providing models of computing and services. Via cloud computing technology, bioinformatics tools can be made available as services to anyone, anywhere, and via any device. Large bio-datasets, highly complex algorithms, computing power demanding analysis methods, and the sudden need for hardware and computational resources provide an ideal environment for large-scale bio-data analysis for cloud computing. Cloud computing is already applied in the fields of biology and biochemistry, via numerous paradigms providing novel ideas stimulating future research. The concept of BioCloud has rapidly emerged with applications related to genomics, drug design, biology tools on the cloud, bio-databases, cloud bio-computing, and numerous applications related to biology and biochemistry. In this chapter, the authors present research results related to biology-related laboratories (BioLabs) as well as potential applications for the everyday clinical routine.

From Cloud Computing to Fog Computing

2021 ◽  
pp. 999-1010
Author(s):  
Sanjay P. Ahuja ◽  
Niharika Deval
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Cost Savings ◽  
End Users ◽  
Internet Technology ◽  
Future Research ◽  
Computing Paradigm ◽  
Key Characteristics ◽  
Iot Devices ◽  
Communication Control

This article describes how in recent years, Cloud Computing has emerged as a fundamental computing paradigm that has significantly changed the approach of enterprises as well as end users towards implementation of Internet technology. The key characteristics such as on-demand resource provision, scalability, rapid elasticity, higher flexibility, and significant cost savings have influenced enterprises of all sizes in the wide and successful adoption of Cloud Computing. Despite numerous advantages, Cloud Computing has its fair share of downsides as well. One of those major concerns is latency issues which has relevance to the Internet of Things (IoT). A new computing paradigm has been proposed by Cisco in early 2014 and termed 'Fog Computing'. Fog Computing otherwise known as Edge Computing is the integration of Cloud Computing and IoT. Being located in close proximity to the IoT devices, the Fog assists with latency requirements of IoT related applications. It also meets the data processing needs of IoT devices which are resource constrained by bringing computation, communication, control and storage closer to the end users. Clouds continue to offer support for data analytics. One can think of the IoT-Fog-Cloud as being part of a continuum. This article surveys the current literature on Fog Computing and provides a discussion on the background, details and architecture of Fog Computing, as well as the application areas of Fog Computing. The article concludes with some recommendations in the areas of future research.

Unique Fog Computing Taxonomy for Evaluating Cloud Services

2021 ◽  
pp. 985-998
Author(s):  
Akashdeep Bhardwaj ◽  
Sam Goundar
Keyword(s):  
Cloud Computing ◽  
Network Model ◽  
Fog Computing ◽  
Research Work ◽  
Cloud Service ◽  
Cloud Services ◽  
Literature Research ◽  
Service Consumer ◽  
Cloud Network ◽  
Best Fit

Fog computing has the potential to resolve cloud computing issues by extending the cloud service provider's reach to the edge of the cloud network model, right up to the cloud service consumer. This enables a whole new state of applications and services which increases the security, enhances the cloud experience, and keeps the data close to the user. This chapter presents a review on the academic literature research work on fog computing, introduces a novel taxonomy to classify cloud products based on fog computing elements, and then determines the best fit fog computing product to choose for the cloud service consumer.

scholarly journals Analysis of an Automatic Early Warning System Based on Fog Architecture

2021 ◽  
Vol 2095 (1) ◽  
pp. 012046
Author(s):  
Gang Shi ◽  
Yuechen Yang
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Early Warning ◽  
Early Warning System ◽  
Fog Computing ◽  
Warning System ◽  
Response Speed ◽  
Computing Architecture ◽  
Computing Services ◽  
Front End

Abstract In the process of analysing and processing terminal sensor information, a large number of terminal sensors are needed to collect front-end information. These front-end data collection, analysis and processing require high real-time, and need the support of location aware mobile computing services. Traditional cloud computing architecture is not the best choice for service scenarios with high real-time requirements. The fog computing architecture is to extend cloud computing services to the edge of the sensor network, coupled with appropriate fitness algorithms, can effectively improve the information analysis and early warning response speed of the geological disaster information early warning system.

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