scholarly journals A Multidomain Standards-Based Fog Computing Architecture for Smart Cities

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Víctor Rampérez ◽  
Javier Soriano ◽  
David Lizcano
Keyword(s):  
Cloud Computing ◽  
Smart Cities ◽  
Fog Computing ◽  
Cost Savings ◽  
Low Latency ◽  
Location Awareness ◽  
Rapid Urbanization ◽  
Computing Architecture ◽  
Computing Paradigm ◽  
Urban Population Growth

Many of the problems arising from rapid urbanization and urban population growth can be solved by making cities “smart”. These smart cities are supported by large networks of interconnected and widely geo-distributed devices, known as Internet of Things or IoT, that generate large volumes of data. Traditionally, cloud computing has been the technology used to support this infrastructure; however, some of the essential requirements of smart cities such as low-latency, mobility support, location-awareness, bandwidth cost savings, and geo-distributed nature of such IoT systems cannot be met. To solve these problems, the fog computing paradigm proposes extending cloud computing models to the edge of the network. However, most of the proposed architectures and frameworks are based on their own private data models and interfaces, which severely reduce the openness and interoperability of these solutions. To address this problem, we propose a standard-based fog computing architecture to enable it to be an open and interoperable solution. The proposed architecture moves the stream processing tasks to the edge of the network through the use of lightweight context brokers and Complex Event Processing (CEP) to reduce latency. Moreover, to communicate the different smart cities domains we propose a Context Broker based on a publish/subscribe middleware specially designed to be elastic and low-latency and exploit the context information of these environments. Additionally, we validate our architecture through a real smart city use case, showing how the proposed architecture can successfully meet the smart cities requirements by taking advantage of the fog computing approach. Finally, we also analyze the performance of the proposed Context Broker based on microbenchmarking results for latency, throughput, and scalability.

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.

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.

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 Integration of Fog and IoT with Multiensor Data Gathering

2019 ◽  
Vol 8 (4) ◽  
pp. 11785-11787
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Fog Computing ◽  
Data Gathering ◽  
Low Latency ◽  
Computing Paradigm ◽  
City System ◽  
Computing Framework ◽  
The City

In the already existing system number of internet connected devices rapidly increase, this increased demand real-time, for the standard cloud computing framework, low latency services proving to be always a challenge. While In the proposed System, fog computing paradigm serves the demands of the latency sensitive applications in the context of IOT. The IOT is rely on cloud computing by passing information about sensor. This is a decentralized process to gather the information from each and every region of the city. System will check the energy and location of every server. Because whenever server uploads the sensor details it can degrade their energy on every time. So we have to migrate the data by allocating another server which contains the energy to send

Fog Computing Application Deployment and Management

2019 ◽  
pp. 68-83
Author(s):  
Ranjitha G. ◽  
Pankaj Lathar ◽  
G. M. Siddesh
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Smart Cities ◽  
Fog Computing ◽  
The Internet ◽  
Access Points ◽  
Computing Paradigm ◽  
Application Deployment ◽  
Iot Devices ◽  
The Internet Of Things

Fog computing enhances cloud computing to be closer to the processes that act on IOT devices. Fogging was introduced to overcome the cloud computing paradigm which was not able to address some services, applications, and other limitations of cloud computing such as security aspects, bandwidth, and latency. Fog computing provides the direct correlation with the internet of things. IBM and CISCO are linking their concepts of internet of things with the help of fog computing. Application services are hosted on the network edge. It improves the efficiency and reduces the amount of data that is transferred to the cloud for analysis, storage, and processing. Developers write the fog application and deploy it to the access points. Several applications like smart cities, healthcare domain, pre-processing, and caching applications have to be deployed and managed properly.

scholarly journals Remote Pain Monitoring Using Fog Computing for e-Healthcare: An Efficient Architecture

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6574
Author(s):  
Syed Rizwan Hassan ◽  
Ishtiaq Ahmad ◽  
Shafiq Ahmad ◽  
Abdullah Alfaify ◽  
Muhammad Shafiq
Keyword(s):  
Cloud Computing ◽  
Monitoring System ◽  
Fog Computing ◽  
Self Report ◽  
Healthcare Applications ◽  
Computing Architecture ◽  
Computing Paradigm ◽  
Smart Healthcare ◽  
Number Of Patients ◽  
Iot Devices

The integration of medical signal processing capabilities and advanced sensors into Internet of Things (IoT) devices plays a key role in providing comfort and convenience to human lives. As the number of patients is increasing gradually, providing healthcare facilities to each patient, particularly to the patients located in remote regions, not only has become challenging but also results in several issues, such as: (i) increase in workload on paramedics, (ii) wastage of time, and (iii) accommodation of patients. Therefore, the design of smart healthcare systems has become an important area of research to overcome these above-mentioned issues. Several healthcare applications have been designed using wireless sensor networks (WSNs), cloud computing, and fog computing. Most of the e-healthcare applications are designed using the cloud computing paradigm. Cloud-based architecture introduces high latency while processing huge amounts of data, thus restricting the large-scale implementation of latency-sensitive e-healthcare applications. Fog computing architecture offers processing and storage resources near to the edge of the network, thus, designing e-healthcare applications using the fog computing paradigm is of interest to meet the low latency requirement of such applications. Patients that are minors or are in intensive care units (ICUs) are unable to self-report their pain conditions. The remote healthcare monitoring applications deploy IoT devices with bio-sensors capable of sensing surface electromyogram (sEMG) and electrocardiogram (ECG) signals to monitor the pain condition of such patients. In this article, fog computing architecture is proposed for deploying a remote pain monitoring system. The key motivation for adopting the fog paradigm in our proposed approach is to reduce latency and network consumption. To validate the effectiveness of the proposed approach in minimizing delay and network utilization, simulations were carried out in iFogSim and the results were compared with the cloud-based systems. The results of the simulations carried out in this research indicate that a reduction in both latency and network consumption can be achieved by adopting the proposed approach for implementing a remote pain monitoring system.

Evolution of Fog Computing and Its Role in IoT Applications

2018 ◽  
pp. 33-52 ◽  
Author(s):  
R. Alageswaran ◽  
S. Miruna Joe Amali
Keyword(s):  
Decision Making ◽  
Cloud Computing ◽  
Real Time ◽  
Fog Computing ◽  
Low Latency ◽  
Location Awareness ◽  
Reasonable Time ◽  
Iot Applications ◽  
Time Interaction ◽  
Geographically Distributed

Fog computing is an evolving technology that brings the benefits achieved by cloud computing to the periphery of the network devices for faster data analytics. This has triggered the usage of fog computing for enabling a new breed of applications and services that require localized and faster decision making. Fog computing has attributes such as location awareness, edge deployment and a large number of geographically distributed nodes, heterogeneity through which fog computing offers better performance in terms of mobility, low latency, and real-time interaction. They can also gracefully handle enormous data flow and provide analytics in reasonable time. Due to these additional attributes, fog computing is considered as the appropriate platform for many applications and especially suited for internet of things (IoT). Fog computing also provides an intelligent platform to manage the distributed and real-time nature of emerging IoT applications and infrastructures. With the increase in the number of connected objects, the development of fog computing is tremendous and has promising technological future growth.

Vehicular Fog Computing Paradigm

2021 ◽  
pp. 1806-1821
Author(s):  
Jyoti Grover
Keyword(s):  
Cloud Computing ◽  
Vehicular Ad Hoc Networks ◽  
Fog Computing ◽  
Location Awareness ◽  
Vehicular Communication ◽  
Open Problems ◽  
Related Services ◽  
Traffic Efficiency ◽  
Computing Paradigm ◽  
Hoc Networks

The main objective of vehicular ad hoc networks (VANETs) is to improve driver safety and traffic efficiency. Most VANET applications are based on periodic exchange of safety messages between nearby vehicles and between vehicles and nearby road side communication units (e.g., traffic lights, road-side lights, etc.). This periodic communication generates huge amount of data that have typical storage, computation, and communication resources needs. In recent years, there has been huge developments in automotive industry, computing, and communication technologies. This has led to vehicular cloud computing (VCC) as a solution to satisfy the requirements of VANETs such as computing, storage, and networking resources. Vehicular fog computing (VFC) is a standard that comprehends cloud computing and related services to the proximity of a network. Since VANET applications have special mobility, low latency, and location awareness requirements, fog computing plays a significant role in VANET applications and services. In urban cities, vehicles parked at shopping malls, offices and similar other places are under-utilized. These can offer great opportunity and value to implement applications of VFC by utilizing vehicles as an infrastructure. In this chapter, we present real time scenarios and applications of VANET that can be implemented using VFC. VANET applications and quality of service can be enhanced by aggregating the resources of these vehicles. We discuss different types of scenarios of moving and parked vehicles as computational, communication, storage and network infrastructures. We have also discussed the challenges and open problems to implement VFC system. This chapter provides the thorough understanding of novel research paradigm and about vehicular communication infrastructures.

Vehicular Fog Computing Paradigm

2018 ◽  
pp. 200-215 ◽  
Author(s):  
Jyoti Grover
Keyword(s):  
Cloud Computing ◽  
Vehicular Ad Hoc Networks ◽  
Fog Computing ◽  
Location Awareness ◽  
Vehicular Communication ◽  
Open Problems ◽  
Related Services ◽  
Traffic Efficiency ◽  
Computing Paradigm ◽  
Hoc Networks

The main objective of vehicular ad hoc networks (VANETs) is to improve driver safety and traffic efficiency. Most VANET applications are based on periodic exchange of safety messages between nearby vehicles and between vehicles and nearby road side communication units (e.g., traffic lights, road-side lights, etc.). This periodic communication generates huge amount of data that have typical storage, computation, and communication resources needs. In recent years, there has been huge developments in automotive industry, computing, and communication technologies. This has led to vehicular cloud computing (VCC) as a solution to satisfy the requirements of VANETs such as computing, storage, and networking resources. Vehicular fog computing (VFC) is a standard that comprehends cloud computing and related services to the proximity of a network. Since VANET applications have special mobility, low latency, and location awareness requirements, fog computing plays a significant role in VANET applications and services. In urban cities, vehicles parked at shopping malls, offices and similar other places are under-utilized. These can offer great opportunity and value to implement applications of VFC by utilizing vehicles as an infrastructure. In this chapter, we present real time scenarios and applications of VANET that can be implemented using VFC. VANET applications and quality of service can be enhanced by aggregating the resources of these vehicles. We discuss different types of scenarios of moving and parked vehicles as computational, communication, storage and network infrastructures. We have also discussed the challenges and open problems to implement VFC system. This chapter provides the thorough understanding of novel research paradigm and about vehicular communication infrastructures.

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