scholarly journals Big Data Integration Method of Mathematical Modeling and Manufacturing System Based on Fog Calculation

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xin Chen
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Integration ◽  
Manufacturing System ◽  
Fog Computing ◽  
Relevant Literature ◽  
Fast Response ◽  
Computing Methods ◽  
Computer Algorithms ◽  
Huge Impact

Using big data to promote economic development, improve social governance, and improve service and regulatory capabilities is becoming a trend. However, the current cloud computing for data processing has been difficult to meet the demand, and the server pressure has increased dramatically, so people pay special attention to the big data integration of fog computing. In order to make the application of big data meet people’s needs, we have established relevant mathematical models based on fog calculation, made system big data integration, collected relevant data, designed experiments, and obtained relevant research data by reviewing relevant literature and interviewing professionals. The research shows that big data integration using fog computing modeling has the characteristics of fast response and stable function. Compared with cloud computing and previous computer algorithms, big data integration has obvious advantages, and the computing speed is nearly 20% faster than cloud computing and about 35% higher than other computing methods. This shows that big data integration built by fog computing can have a huge impact on people’s lives.

scholarly journals Cloud Computing in Singapore: Key Drivers and Recommendations for a Smart Nation

2018 ◽  
Vol 6 (4) ◽  
pp. 39-47 ◽  
Author(s):  
Reuben Ng
Keyword(s):  
Public Policy ◽  
Cloud Computing ◽  
Big Data ◽  
Business Models ◽  
Fog Computing ◽  
Novel Technologies ◽  
Cloud Computing Adoption ◽  
Big Data Applications ◽  
Key Drivers ◽  
The Government

Cloud computing adoption enables big data applications in governance and policy. Singapore’s adoption of cloud computing is propelled by five key drivers: (1) public demand for and satisfaction with e-government services; (2) focus on whole-of-government policies and practices; (3) restructuring of technology agencies to integrate strategy and implementation; (4) building the Smart Nation Platform; (5) purpose-driven cloud applications especially in healthcare. This commentary also provides recommendations to propel big data applications in public policy and management: (a) technologically, embrace cloud analytics, and explore “fog computing”—an emerging technology that enables on-site data sense-making before transmission to the cloud; (b) promote regulatory sandboxes to experiment with policies that proactively manage novel technologies and business models that may radically change society; (c) on the collaboration front, establish unconventional partnerships to co-innovate on challenges like the skills-gap—an example is the unprecedented partnership led by the Lee Kuan Yew School of Public Policy with the government, private sector and unions.

Vehicular Cloud and Fog Computing Architecture, Applications, Services, and Challenges

2020 ◽  
pp. 268-296
Author(s):  
Priyanka Gaba ◽  
Ram Shringar Raw
Keyword(s):  
Cloud Computing ◽  
High Speed ◽  
Fog Computing ◽  
Detailed Comparison ◽  
Fast Response ◽  
Computing Technique ◽  
Vehicular Cloud ◽  
Network Bandwidth ◽  
Real Time Applications ◽  
Safety Features

VANET, a type of MANET, connects vehicles to provide safety and non-safety features to the drivers and passengers by exchanging valuable data. As vehicles on road are increasing to handle such data cloud computing, functionality is merged with vehicles known as Vehicular Cloud Computing(VCC) to serve VANET with computation, storage, and networking functionalities. But Cloud, a centralized server, does not fit well for vehicles needing high-speed processing, low latency, and more security. To overcome these limitations of Cloud, Fog computing was evolved, extending the functionality of cloud computing model to the edge of the network. This works well for real time applications that need fast response, saves network bandwidth, and is a reliable, secure solution. An application of Fog is with vehicles known as Vehicular Fog Computing (VFC). This chapter discusses cloud computing technique and its benefits and drawbacks, detailed comparison between VCC and VFC, applications of Fog Computing, its security, and forensic challenges.

Emerging Trends in Cloud Computing, Big Data, Fog Computing, IoT and Smart Living

2017 ◽  
pp. 29-40 ◽  
Author(s):  
Amin Hosseinian-Far ◽  
Muthu Ramachandran ◽  
Charlotte Lilly Slack
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Fog Computing ◽  
Emerging Trends ◽  
Smart Living

scholarly journals Fog-IBDIS: Industrial Big Data Integration and Sharing with Fog Computing for Manufacturing Systems

Engineering ◽  
2019 ◽  
Vol 5 (4) ◽  
pp. 662-670 ◽  
Author(s):  
Junliang Wang ◽  
Peng Zheng ◽  
Youlong Lv ◽  
Jingsong Bao ◽  
Jie Zhang
Keyword(s):  
Big Data ◽  
Data Integration ◽  
Manufacturing Systems ◽  
Fog Computing ◽  
Industrial Big Data

scholarly journals Research and Application of Cloud Computing and Big Data Technology

2021 ◽  
Vol 2083 (4) ◽  
pp. 042087
Author(s):  
Bingran Hui
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Data Integration ◽  
Modern Society ◽  
Data Governance ◽  
Combined Application ◽  
Integration Data ◽  
Network Technologies ◽  
Big Data Technology

Abstract The combined application of new network technologies with the traditional Internet and industry has enabled new businesses such as the Internet of Things and cloud computing to be gradually derived. To realize the construction of a modern society in China, great attention should be paid to the application of new network technologies such as cloud computing in actual work. Now through data integration and correlation analysis, the accuracy and innovation of information are further realized, and the overall work efficiency and work quality are improved. This paper systematically analyzes the network big data technology and applications of cloud computing and Internet of Things, and conducts research from data collection, data integration, data processing, and data governance. Its main purpose is to make the value and function of these new network technologies fully utilized

Fog Computing Architecture for Scalable Processing of Geospatial Big Data

2020 ◽  
Vol 11 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Rabindra K. Barik ◽  
Rojalina Priyadarshini ◽  
Rakesh K. Lenka ◽  
Harishchandra Dubey ◽  
Kunal Mankodiya
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Analysis ◽  
Case Studies ◽  
Information Management ◽  
Fog Computing ◽  
Geospatial Data ◽  
Raspberry Pi ◽  
Ganga Basin ◽  
Tourism Information

Geospatial data analysis using cloud computing platform is one of the promising areas for analysing, retrieving, and processing volumetric data. Fog computing paradigm assists cloud platform where fog devices try to increase the throughput and reduce latency at the edge of the client. In this research paper, the authors discuss two case studies on geospatial data analysis using Fog-assisted cloud computing namely, (1)Ganga River Basin Management System; and (2)Tourism Information Management of India. Both case studies evaluate proposed GeoFog architecture for efficient analysis and management of geospatial big data employing fog computing. The authors developed a prototype of GeoFog architecture using Intel Edison and Raspberry Pi devices. The authors implemented some of the open source compression methods for reducing the data transmission overload in the cloud. Proposed architecture performs data compression and overlay analysis of data. The authors further discussed the improvement in scalability and time analysis using proposed GeoFog architecture and Geospark tool. Discussed results show the merit of fog computing that holds an enormous promise for enhanced analysis of geospatial big data in river Ganga basin and tourism information management scenario.

scholarly journals The Purview of Blockchain Appositeness in Computing Paradigms: A Survey

2021 ◽  
Vol 26 (1) ◽  
pp. 33-46
Author(s):  
Battula V. Satish Babu ◽  
Kare Suresh Babu
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Quantum Computing ◽  
Fog Computing ◽  
Research Articles ◽  
Privacy And Security ◽  
Research Opportunities ◽  
Blockchain Technology ◽  
Integration Problems ◽  
Big Data Computing

Blockchain technology is getting more and more pertinent to solve most of the digital problems that we face today. Blockchain is notable for its prominent features like immutability, decentralization, consensus, privacy, and security. However, blockchain is still suffering from different barriers like quantum attacks, scalability problems, integration problems, incompetence to face bigdata, storage problems, and so on. The main aim of this study was to find out the scope, various problems raised, and the applicability of blockchain technology when integrated with different computing paradigms like cloud computing, edge computing, fog computing, osmotic computing, big data computing, and quantum computing. To conduct this study, we have surveyed different research articles in the combination of blockchain technology and computing paradigms. Based on this survey, we have mentioned the contemporary research works, challenges, and a list of possible research opportunities and solutions.

scholarly journals From Cloud Computing to Fog Computing (C2F): The key technology provides services in health care big data

2018 ◽  
Vol 189 ◽  
pp. 03010 ◽  
Author(s):  
Babur Hayat Malik ◽  
Sadaf Nawaz Cheema ◽  
Iqra Iqbal ◽  
Yasar Mahmood ◽  
Majid Ali ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Social Networking ◽  
Fog Computing ◽  
Storage Space ◽  
Medical Field ◽  
Web Based ◽  
Key Technology ◽  
Points Of Interest ◽  
Processing Mechanism

Because of the broad utilization of web-based social networking, data is produces by the fast increment. Big Data is giving the office to accumulate, store, oversee and examine information in colossal volume that is produced through the healthcare system. Cloud Computing is an advancement too that insures the fulfillment of IT requirements in a suitable way by providing the cloud-based environment for medical field. Storage is an immense issue for BD, volume of data is huge, this issue may resolve with the help of cloud computing by providing the storage space for data and processing mechanism as well. This paper presents these thoughts with respects to medicinal services. It tells regarding the points of interest, yet in addition challenges conveyed by Big Data to this field. It additionally talks about the idea of fog computing, some advantages of edge computing on cloud computing and deliberate the architecture of fog computing for healthcare and services provides by that architecture.

scholarly journals A Comprehensive Study of Caching Effects on Fog Computing Performance

2021 ◽  
pp. 1-18
Author(s):  
Marwa Mahfodh Abdulqadir ◽  
Azar Abid Salih ◽  
Omar M. Ahmed ◽  
Dathar Abas Hasan ◽  
Lailan M. Haji ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Data Storage ◽  
Fog Computing ◽  
Middle Layer ◽  
Fast Response ◽  
The Internet ◽  
Main Task ◽  
Reference Architecture ◽  
The Internet Of Things

The rapid advancement in the Internet of things applications generates a considerable amount of data and requires additional computing power. These are serious challenges that directly impact the performance, latency, and network breakdown of cloud computing. Fog Computing can be depended on as an excellent solution to overcome some related problems in cloud computing. Fog computing supports cloud computing to become nearer to the Internet of Things. The fog's main task is to access the data generated by the IoT devices near the edge. The data storage and data processing are performed locally at the fog nodes instead of achieving that at cloud servers. Fog computing presents high-quality services and fast response time. Therefore, Fog computing can be the best solution for the Internet of things to present a practical and secure service for various clients. Fog computing enables sufficient management for the services and resources by keeping the devices closer to the network edge. In this paper, we review various computing paradigms, features of fog computing, an in-depth reference architecture of fog with its various levels, a detailed analysis of fog with different applications, various fog system algorithms, and also systematically examines the challenges in Fog Computing which act as a middle layer between IoT sensors or devices and data centers of the cloud.

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