Feedback-Based Fuzzy Resource Management in IoT-Based-Cloud

2020 ◽  
Vol 3 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Basetty Mallikarjuna
Keyword(s):  
Fog Computing ◽  
High Volume ◽  
Cloud Services ◽  
Dynamic Feedback ◽  
Smart Cameras ◽  
Computing Paradigm ◽  
Qos Parameters ◽  
Speed Up ◽  
Iot Devices ◽  
Smart Home Appliances

The main aim of Internet of Things (IoT) is to get every “thing” (sensors, smart cameras, wearable devices, and smart home appliances) to connect to the internet. Henceforth to produce the high volume of data required for data processing between IoT devices, large storage and the huge number of applications to offer cloud computing as a service. The purpose of IoT-based-cloud is to manage the resources, and effective utilization of tasks in cloud. The end user applications are essential to enhance the QoS parameters. As per the QoS parameters, the service provider makes the speed up of tasks. There is a requirement for assigning responsibilities based on priority. The cloud services are increased to the network edge, and the planned model is under the Fog computing paradigm to reduce the makespan of time. The priority based fuzzy scheduling approach is brought by the dynamic feedback-based mechanism. The planned mechanism is verified with the diverse prevailing algorithms and evidenced that planned methodology is supported by effective results.

Examining IoT's Applications Using Cloud Services

2018 ◽  
pp. 147-163 ◽  
Author(s):  
Saravanan K ◽  
P. Srinivasan
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Distributed Computing ◽  
Knowledge Sharing ◽  
Effective Communication ◽  
Cloud Services ◽  
On Demand ◽  
Computing Paradigm ◽  
Iot Devices ◽  
And Storage

Cloud IoT has evolved from the convergence of Cloud computing with Internet of Things (IoT). The networked devices in the IoT world grow exponentially in the distributed computing paradigm and thus require the power of the Cloud to access and share computing and storage for these devices. Cloud offers scalable on-demand services to the IoT devices for effective communication and knowledge sharing. It alleviates the computational load of IoT, which makes the devices smarter. This chapter explores the different IoT services offered by the Cloud as well as application domains that are benefited by the Cloud IoT. The challenges on offloading the IoT computation into the Cloud are also discussed.

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.

scholarly journals A survey on fog computing: research challenges in security and privacy issues

2018 ◽  
Vol 7 (2.7) ◽  
pp. 335 ◽  
Author(s):  
T Veerraju ◽  
Dr K. Kiran Kumar
Keyword(s):  
Fog Computing ◽  
Cloud Services ◽  
Security And Privacy ◽  
Limited Resources ◽  
Privacy And Security ◽  
Computing Paradigm ◽  
Is Security ◽  
Real Time Applications ◽  
And Storage ◽  
Privacy Issues

With the rapid advancement of Internet of Things has enabled to combine the intercommunication and interconnection between seamless networks. Cloud computing provides backend solutions and one among the most prominent technologies for the users, still cannot be solved all the problems such as latency of real time applications. However, a new computing paradigm comes in to the picture. Many of the researchers focused on this exemplar known as Fog/Edge computing, which has been planned to the extension of cloud services. Fog provides the services to the edge of the networks, which makes communication, computation and storage for end users through fog devices and for servers like controllers. We analyze the study, which aims to augment low bandwidth, latency along with the privacy and security.   The major problem in the Fog computing is security due to the limited resources. In this paper, we investigated the protection issues and confrontation of Fog and also provide countermeasures on security for different attacks. We focused the future security directions and challenges to address in fog networks.

scholarly journals A Fog Computing Architecture with Multi-Layer for Computing-Intensive IoT Applications

2021 ◽  
Vol 11 (24) ◽  
pp. 11585
Author(s):  
Muhammad Muneeb ◽  
Kwang-Man Ko ◽  
Young-Hoon Park
Keyword(s):  
Artificial Intelligence ◽  
Data Analysis ◽  
New Technologies ◽  
Fog Computing ◽  
Layered Architecture ◽  
Computing Platform ◽  
Computing Paradigm ◽  
Iot Devices ◽  
Analysis System ◽  
Data Analysis System

The emergence of new technologies and the era of IoT which will be based on compute-intensive applications. These applications will increase the traffic volume of today’s network infrastructure and will impact more on emerging Fifth Generation (5G) system. Research is going in many details, such as how to provide automation in managing and configuring data analysis tasks over cloud and edges, and to achieve minimum latency and bandwidth consumption with optimizing task allocation. The major challenge for researchers is to push the artificial intelligence to the edge to fully discover the potential of the fog computing paradigm. There are existing intelligence-based fog computing frameworks for IoT based applications, but research on Edge-Artificial Intelligence (Edge-AI) is still in its initial stage. Therefore, we chose to focus on data analytics and offloading in our proposed architecture. To address these problems, we have proposed a prototype of our architecture, which is a multi-layered architecture for data analysis between cloud and fog computing layers to perform latency- sensitive analysis with low latency. The main goal of this research is to use this multi-layer fog computing platform for enhancement of data analysis system based on IoT devices in real-time. Our research based on the policy of the OpenFog Consortium which will offer the good outcomes, but also surveillance and data analysis functionalities. We presented through case studies that our proposed prototype architecture outperformed the cloud-only environment in delay-time, network usage, and energy consumption.

scholarly journals Fog-Based CDN Framework for Minimizing Latency of Web Services Using Fog-Based HTTP Browser

2021 ◽  
Vol 13 (12) ◽  
pp. 320
Author(s):  
Ahmed H. Ibrahim ◽  
Zaki T. Fayed ◽  
Hossam M. Faheem
Keyword(s):  
Cloud Computing ◽  
Web Services ◽  
Fog Computing ◽  
Partial Solution ◽  
Cloud Services ◽  
Network Layer ◽  
Cloud Data ◽  
Download Time ◽  
Computing Paradigm ◽  
Cloud Servers

Cloud computing has been a dominant computing paradigm for many years. It provides applications with computing, storage, and networking capabilities. Furthermore, it enhances the scalability and quality of service (QoS) of applications and offers the better utilization of resources. Recently, these advantages of cloud computing have deteriorated in quality. Cloud services have been affected in terms of latency and QoS due to the high streams of data produced by many Internet of Things (IoT) devices, smart machines, and other computing devices joining the network, which in turn affects network capabilities. Content delivery networks (CDNs) previously provided a partial solution for content retrieval, availability, and resource download time. CDNs rely on the geographic distribution of cloud servers to provide better content reachability. CDNs are perceived as a network layer near cloud data centers. Recently, CDNs began to perceive the same degradations of QoS due to the same factors. Fog computing fills the gap between cloud services and consumers by bringing cloud capabilities close to end devices. Fog computing is perceived as another network layer near end devices. The adoption of the CDN model in fog computing is a promising approach to providing better QoS and latency for cloud services. Therefore, a fog-based CDN framework capable of reducing the load time of web services was proposed in this paper. To evaluate our proposed framework and provide a complete set of tools for its use, a fog-based browser was developed. We showed that our proposed fog-based CDN framework improved the load time of web pages compared to the results attained through the use of the traditional CDN. Different experiments were conducted with a simple network topology against six websites with different content sizes along with a different number of fog nodes at different network distances. The results of these experiments show that with a fog-based CDN framework offloading autonomy, latency can be reduced by 85% and enhance the user experience of websites.

scholarly journals Fog Computing: An Overview of Big IoT Data Analytics

2018 ◽  
Vol 2018 ◽  
pp. 1-22 ◽  
Author(s):  
Muhammad Rizwan Anawar ◽  
Shangguang Wang ◽  
Muhammad Azam Zia ◽  
Ahmer Khan Jadoon ◽  
Umair Akram ◽  
...  
Keyword(s):  
Data Analytics ◽  
Smart Cities ◽  
Fog Computing ◽  
Computing Paradigm ◽  
Key Characteristics ◽  
Challenges And Opportunities ◽  
Cloud Framework ◽  
Iot Devices ◽  
Health Care Monitoring ◽  
Computing Structure

A huge amount of data, generated by Internet of Things (IoT), is growing up exponentially based on nonstop operational states. Those IoT devices are generating an avalanche of information that is disruptive for predictable data processing and analytics functionality, which is perfectly handled by the cloud before explosion growth of IoT. Fog computing structure confronts those disruptions, with powerful complement functionality of cloud framework, based on deployment of micro clouds (fog nodes) at proximity edge of data sources. Particularly big IoT data analytics by fog computing structure is on emerging phase and requires extensive research to produce more proficient knowledge and smart decisions. This survey summarizes the fog challenges and opportunities in the context of big IoT data analytics on fog networking. In addition, it emphasizes that the key characteristics in some proposed research works make the fog computing a suitable platform for new proliferating IoT devices, services, and applications. Most significant fog applications (e.g., health care monitoring, smart cities, connected vehicles, and smart grid) will be discussed here to create a well-organized green computing paradigm to support the next generation of IoT applications.

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.

scholarly journals Study of the Efficiency of Fog Computing in an Optimized LoRaWAN Cloud Architecture

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3159
Author(s):  
Jakub Jalowiczor ◽  
Jan Rozhon ◽  
Miroslav Voznak
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
The Internet ◽  
Long Distance ◽  
Daily Lives ◽  
Communication Architecture ◽  
Computing Paradigm ◽  
Data Volume ◽  
Distance Communication ◽  
Iot Devices

The technologies of the Internet of Things (IoT) have an increasing influence on our daily lives. The expansion of the IoT is associated with the growing number of IoT devices that are connected to the Internet. As the number of connected devices grows, the demand for speed and data volume is also greater. While most IoT network technologies use cloud computing, this solution becomes inefficient for some use-cases. For example, suppose that a company that uses an IoT network with several sensors to collect data within a production hall. The company may require sharing only selected data to the public cloud and responding faster to specific events. In the case of a large amount of data, the off-loading techniques can be utilized to reach higher efficiency. Meeting these requirements is difficult or impossible for solutions adopting cloud computing. The fog computing paradigm addresses these cases by providing data processing closer to end devices. This paper proposes three possible network architectures that adopt fog computing for LoRaWAN because LoRaWAN is already deployed in many locations and offers long-distance communication with low-power consumption. The architecture proposals are further compared in simulations to select the optimal form in terms of total service time. The resulting optimal communication architecture could be deployed to the existing LoRaWAN with minimal cost and effort of the network operator.

scholarly journals Data Deduplication for Efficient Storage on Cloud using Fog Computing Paradigm

2020 ◽  
Vol 9 (1) ◽  
pp. 812-815
Keyword(s):  
Cloud Computing ◽  
Data Compression ◽  
Distributed System ◽  
Fog Computing ◽  
Geographic Area ◽  
Cloud Services ◽  
Data Deduplication ◽  
Computing Paradigm ◽  
Efficient Storage ◽  
Large Geographic Area

Cloud services have taken the IT world by storm by making its services available to everyone over large geographic area. With the increasing amount of data generate every minute it has become increasing difficult to manage resources and the storage. Thus, data compression techniques like data de duplication that aims at executing the redundancy of data and forming chunks of data that can be stored on a distributed system can be proved to a logistic solution. But when it comes to cloud problems like security has always been a major issue. In order to eliminate these challenges, we need to implement a layer of fog computing they would deal with the shortcomings of cloud computing and at the same time present a filtration front before the incoming data.

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.

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