scholarly journals A New Edge Computing based Cloud System for IoT Applications

2019 ◽  
Vol 8 (2) ◽  
pp. 4289-4293
Keyword(s):  
Cloud Computing ◽  
Spectral Efficiency ◽  
Telecommunication Network ◽  
Fog Computing ◽  
Mobile Internet ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Novel Technology ◽  
Different Characteristics ◽  
The Internet Of Things

The mobile internet and the internet of things (IoT) has emerged out with various applications were centralized cloud computing has faced several challenges over the past years. Challenges include high latency and low Spectral Efficiency. Nevertheless, these challenges can be faced using a novel technology which is now emerging out as a major trending technology that supersedes centralized cloud computing with edge devices of networks. Well, this technology will reduce the latency and will enhance spectral efficiency and will also support massive machine types of communication. A detailed description of this trending technology deals with mobile edge computing, cloudlets and fog computing. In addition, the functioning process of each computing technology is also included. The different characteristics of mobile edge computing and fog computing have been focused. However the most significant part of how these technologies work under the discussion of telecommunication network is also briefly explained.

scholarly journals Application of Basketball Training System Based on Dynamic Intelligent Fog Computing Network

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Ke Yang
Keyword(s):  
Genetic Algorithm ◽  
Fog Computing ◽  
Academic Community ◽  
Training System ◽  
Mobile Internet ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Transmission Distance ◽  
Test Input ◽  
On The Road

Although the development of the mobile Internet and the Internet of Things has greatly promoted the progress and development of society, it has also created many problems for people on the road of scientific and technological exploration. In order to meet the problems and requirements of high bandwidth, high load, and low latency in the current network development, the emergence of the concept of mobile edge computing has attracted extensive attention from the academic community. This article focuses on the representative mode of mobile edge computing-fog computing (in this model, data, (data)processing, and applications are concentrated in devices at the edge of the network, instead of being stored almost entirely in the cloud). By applying it to the development and operation of basketball training system, it explores the performance of dynamic intelligent fog computing in intelligent end user services. This paper proposes a fog resource scheduling scheme based on linear weighted genetic algorithm, which converts the problem of multiobjective optimization into a single-objective optimization problem. When applying the genetic algorithm based on weighted sum, preference is given to delay, communication load, and service cost. Value is integrated into an objective function to perform genetic operations to get a better solution. From the experimental data, the system can support 20 DCTU terminals with a pressure request of 10 messages per second per terminal under the pressure environment created by the pressure test input data. The barrier-free transmission distance is 200 m, and the barrier transmission distance is 50 m. It has strong fault tolerance.

scholarly journals A Survey on Mobile Edge Computing: Focusing on Service Adoption and Provision

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Kai Peng ◽  
Victor C. M. Leung ◽  
Xiaolong Xu ◽  
Lixin Zheng ◽  
Jiabin Wang ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Mobile Networks ◽  
Edge Computing ◽  
Computation Offloading ◽  
Battery Life ◽  
Mobile Edge Computing ◽  
Service Adoption ◽  
Comprehensive Survey ◽  
And Storage ◽  
Execution Delay

Mobile cloud computing (MCC) integrates cloud computing (CC) into mobile networks, prolonging the battery life of the mobile users (MUs). However, this mode may cause significant execution delay. To address the delay issue, a new mode known as mobile edge computing (MEC) has been proposed. MEC provides computing and storage service for the edge of network, which enables MUs to execute applications efficiently and meet the delay requirements. In this paper, we present a comprehensive survey of the MEC research from the perspective of service adoption and provision. We first describe the overview of MEC, including the definition, architecture, and service of MEC. After that we review the existing MUs-oriented service adoption of MEC, i.e., offloading. More specifically, the study on offloading is divided into two key taxonomies: computation offloading and data offloading. In addition, each of them is further divided into single MU offloading scheme and multi-MU offloading scheme. Then we survey edge server- (ES-) oriented service provision, including technical indicators, ES placement, and resource allocation. In addition, other issues like applications on MEC and open issues are investigated. Finally, we conclude the paper.

scholarly journals IoT-Fog A Communication Framework using Blockchain in the Internet of Things

2020 ◽  
Author(s):  
Tanweer Alam
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Fog Computing ◽  
Emerging Technology ◽  
Smart Devices ◽  
The Internet ◽  
Next Generation ◽  
Communication Framework ◽  
Generation Computing ◽  
The Internet Of Things

<p>The fog computing is the emerging technology to compute, store, control and connecting smart devices with each other using cloud computing. The Internet of Things (IoT) is an architecture of uniquely identified interrelated physical things, these physical things are able to communicate with each other and can transmit and receive information. <a>This research presents a framework of the combination of the Internet of Things (IoT) and Fog computing. The blockchain is also the emerging technology that provides a hyper, distributed, public, authentic ledger to record the transactions. Blockchains technology is a secured technology that can be a boon for the next generation computing. The combination of fog, blockchains, and IoT creates a new opportunity in this area. In this research, the author presents a middleware framework based on the blockchain, fog, and IoT. The framework is implemented and tested. The results are found positive. </a></p>

Introduction to Fog Computing

2019 ◽  
pp. 1-35
Author(s):  
Stojan Kitanov ◽  
Toni Janevski
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Fog Computing ◽  
High Mobility ◽  
End Users ◽  
Mobile Edge Computing ◽  
New Paradigm ◽  
Research Directions ◽  
Intelligent Networking ◽  
High Scalability

Pushing computing, control, data storage, and processing into the cloud has been a key trend in the past decade. However, the cloud alone encounters growing limitations, such as reduced latency, high mobility, high scalability, and real-time execution in order to meet the upcoming computing and intelligent networking demands. A new paradigm called fog computing has emerged to overcome these limits. Fog extends cloud computing and services to the edge of the network. It provides data, computing, storage, and application services to end-users that can be hosted at the network edge. It reduces service latency, and improves QoS/QoE, that results in superior user experience. This chapter is about introduction and overview of fog computing, comparison between fog computing and cloud computing, fog computing and mobile edge computing, possible fog computing architecture, applications of fog computing, and possible research directions.

The Role of Edge/Fog Computing Security in IoT and Industry 4.0 Infrastructures

2021 ◽  
pp. 211-222
Author(s):  
Meltem Mutluturk ◽  
Burcu Kor ◽  
Bilgin Metin
Keyword(s):  
Cloud Computing ◽  
Information And Communication Technologies ◽  
Industry 4.0 ◽  
Fog Computing ◽  
Communication Technologies ◽  
The Internet ◽  
Current State ◽  
Information And Communication ◽  
The Internet Of Things

The development of information and communication technologies (ICT) has led to many innovative technologies. The integration of technologies such as the internet of things (IoT), cloud computing, and machine learning concepts have given rise to Industry 4.0. Fog and edge computing have stepped in to fill the areas where cloud computing is inadequate to ensure these systems work quickly and efficiently. The number of connected devices has brought about cybersecurity issues. This study reviewed the current literature regarding edge/fog-based cybersecurity in IoT to display the current state.

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.

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