Fog-Assisted Healthcare Framework for Smart Hospital Environment

2021 ◽  
Author(s):  
Tariq Ahanger
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Health Assessment ◽  
Health Condition ◽  
Current Paper ◽  
Hospital Environment ◽  
Computing Paradigm ◽  
Network Utilization ◽  
Effective Performance ◽  
Computational Platform

Abstract The technological revolution brought by the Internet of Things (IoT) has mostly relied on cloud computing. However, to satisfy the demands of timesensitive services in the medical industry, Fog Computing, a novel computational platform based on the cloud computing paradigm, has shown to be a useful tool by extending cloud resources to the network’s edge. The current paper examines the role of the fog paradigm in the domain of healthcare decision-making, focusing on its primary advantages in terms of latency, network utilization, and power consumption. A fog-computing based health assessment framework is developed in the current paper. Moreover, based on effective performance parameters, the performance is evaluated and depicted. The results show that the presented strategy can reduce network congestion of the communication network by analyzing information at the local node. Moreover, increased security on health information can be maintained at local fog-node and enhanced data protection from unauthorized access can be acquired. Fog computing offers greater insights into the health condition of patients with enhanced accuracy, precision, reliability and stability.

scholarly journals Fog Computing Framework for Smart City Design

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.

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 Fog Computing Resource Optimization: A Review on Current Scenarios and Resource Management

2019 ◽  
Vol 16 (2) ◽  
pp. 0419 ◽  
Author(s):  
Dar Et al.
Keyword(s):  
Cloud Computing ◽  
Resource Management ◽  
Fog Computing ◽  
Energy Resource ◽  
Optimization Methods ◽  
Resource Optimization ◽  
Data Generation ◽  
Computing Paradigm ◽  
Processing Power ◽  
Huge Data

            The unpredictable and huge data generation nowadays by smart computing devices like (Sensors, Actuators, Wi-Fi routers), to handle and maintain their computational processing power in real time environment by centralized cloud platform is difficult because of its limitations, issues and challenges, to overcome these, Cisco introduced the Fog computing paradigm as an alternative for cloud-based computing. This recent IT trend is taking the computing experience to the next level. It is an extended and advantageous extension of the centralized cloud computing technology. In this article, we tried to highlight the various issues that currently cloud computing is facing. Here in this research article, we present a comprehensive review of fog computing, differentiating it from cloud computing, also present various use-cases of fog computing in different domains, we came to conclude that Fog computing leads in an efficient energy resource management, leveraging the energy both in terms of consumption and cost scenarios. Further, we highlighted its key features, challenges and issues, resource optimization methods.

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.

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.

Fog Computing

Fog Computing ◽  
2018 ◽  
pp. 198-207 ◽  
Author(s):  
Chintan M. Bhatt ◽  
C. K. Bhensdadia
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Real Time ◽  
Fog Computing ◽  
The Internet ◽  
Research Issues ◽  
Computing Paradigm ◽  
Time Interaction ◽  
Edge Network ◽  
The Internet Of Things

The Internet of Things could be a recent computing paradigm, defined by networks of extremely connected things – sensors, actuators and good objects – communication across networks of homes, buildings, vehicles, and even individuals whereas cloud computing could be ready to keep up with current processing and machine demands. Fog computing provides architectural resolution to deal with some of these issues by providing a layer of intermediate nodes what's referred to as an edge network [26]. These edge nodes provide interoperability, real-time interaction, and if necessary, computational to the Cloud. This paper tries to analyse different fog computing functionalities, tools and technologies and research issues.

scholarly journals Fog Computing Resource Optimization: A Review on Current Scenarios and Resource Management

2019 ◽  
Vol 16 (2) ◽  
pp. 0419
Author(s):  
Dar Et al.
Keyword(s):  
Cloud Computing ◽  
Resource Management ◽  
Fog Computing ◽  
Energy Resource ◽  
Optimization Methods ◽  
Resource Optimization ◽  
Data Generation ◽  
Computing Paradigm ◽  
Processing Power ◽  
Huge Data

            The unpredictable and huge data generation nowadays by smart computing devices like (Sensors, Actuators, Wi-Fi routers), to handle and maintain their computational processing power in real time environment by centralized cloud platform is difficult because of its limitations, issues and challenges, to overcome these, Cisco introduced the Fog computing paradigm as an alternative for cloud-based computing. This recent IT trend is taking the computing experience to the next level. It is an extended and advantageous extension of the centralized cloud computing technology. In this article, we tried to highlight the various issues that currently cloud computing is facing. Here in this research article, we present a comprehensive review of fog computing, differentiating it from cloud computing, also present various use-cases of fog computing in different domains, we came to conclude that Fog computing leads in an efficient energy resource management, leveraging the energy both in terms of consumption and cost scenarios. Further, we highlighted its key features, challenges and issues, resource optimization methods.

Sign in / Sign up

Export Citation Format

Share Document