scholarly journals Fog Computing: Enabling the Management and Orchestration of Smart City Applications in 5G Networks

Entropy ◽  
2017 ◽  
Vol 20 (1) ◽  
pp. 4 ◽  
Author(s):  
◽  
◽  
◽  
Keyword(s):  
Smart City ◽  
Fog Computing ◽  
5G Networks

M2FBalancer: A mist-assisted fog computing-based load balancing strategy for smart cities

2021 ◽  
pp. 1-15
Author(s):  
Subhranshu Sekhar Tripathy ◽  
Diptendu Sinha Roy ◽  
Rabindra K. Barik
Keyword(s):  
Load Balancing ◽  
Resource Utilization ◽  
Smart City ◽  
Load Transfer ◽  
Smart Cities ◽  
Fog Computing ◽  
Round Robin ◽  
Healthcare Management ◽  
Optimization Strategy ◽  
Allocation Method

Nowadays, cities are intended to change to a smart city. According to recent studies, the use of data from contributors and physical objects in many cities play a key element in the transformation towards a smart city. The ‘smart city’ standard is characterized by omnipresent computing resources for the observing and critical control of such city’s framework, healthcare management, environment, transportation, and utilities. Mist computing is considered a computing prototype that performs IoT applications at the edge of the network. To maintain the Quality of Service (QoS), it is impressive to employ context-aware computing as well as fog computing simultaneously. In this article, the author implements an optimization strategy applying a dynamic resource allocation method based upon genetic algorithm and reinforcement learning in combination with a load balancing procedure. The proposed model comprises four layers i.e. IoT layer, Mist layer, Fog layer, and Cloud layer. Authors have proposed a load balancing technique called M2F balancer which regulates the traffic in the network incessantly, accumulates the information about each server load, transfer the incoming query, and disseminate them among accessible servers equally using dynamic resources allocation method. To validate the efficacy of the proposed algorithm makespan, resource utilization, and the degree of imbalance (DOI) are considered as the scheduling parameter. The proposed method is being compared with the Least count, Round Robin, and Weighted Round Robin. In the end, the results demonstrate that the solutions enhance QoS in the mist assisted cloud environment concerning maximization resource utilization and minimizing the makespan. Therefore, M2FBalancer is an effective method to utilize the resources efficiently by ensuring uninterrupted service. Consequently, it improves performance even at peak times.

Quality Evaluation of Cloud and Fog Computing Services in 5G Networks

2019 ◽  
pp. 1-36 ◽  
Author(s):  
Stojan Kitanov ◽  
Borislav Popovski ◽  
Toni Janevski
Keyword(s):  
Network Performance ◽  
Fog Computing ◽  
High Mobility ◽  
Network Control ◽  
5G Networks ◽  
New Paradigm ◽  
Network Function ◽  
Computing Services ◽  
5G Network ◽  
Intelligent Networking

Because of the increased computing and intelligent networking demands in 5G network, cloud computing alone encounters too many limitations, such as requirements for reduced latency, high mobility, high scalability, and real-time execution. A new paradigm called fog computing has emerged to resolve these issues. Fog computing distributes computing, data processing, and networking services to the edge of the network, closer to end users. Fog applied in 5G significantly improves network performance in terms of spectral and energy efficiency, enable direct device-to-device wireless communications, and support the growing trend of network function virtualization and separation of network control intelligence from radio network hardware. This chapter evaluates the quality of cloud and fog computing services in 5G network, and proposes five algorithms for an optimal selection of 5G RAN according to the service requirements. The results demonstrate that fog computing is a suitable technology solution for 5G networks.

Fog Computing Based Architecture for Smart City Projects and Applications

2021 ◽  
pp. 191-213
Author(s):  
Naishadh Mehta ◽  
Anand Ruparelia ◽  
Jai Prakash Verma
Keyword(s):  
Smart City ◽  
Fog Computing

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.

A Blockchain-SDN-Enabled Internet of Vehicles Environment for Fog Computing and 5G Networks

2020 ◽  
Vol 7 (5) ◽  
pp. 4278-4291 ◽  
Author(s):  
Jianbin Gao ◽  
Kwame Opuni-Boachie Obour Agyekum ◽  
Emmanuel Boateng Sifah ◽  
Kingsley Nketia Acheampong ◽  
Qi Xia ◽  
...  
Keyword(s):  
Fog Computing ◽  
5G Networks ◽  
Internet Of Vehicles
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