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 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.

A Security-By-Distribution Approach to Manage Big Data in a Federation of Untrustworthy Clouds

2019 ◽  
pp. 346-375
Author(s):  
Jens Kohler ◽  
Christian Richard Lorenz ◽  
Markus Gumbel ◽  
Thomas Specht ◽  
Kiril Simov
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Cost Savings ◽  
Cloud Provider ◽  
Small Data ◽  
Storage Space ◽  
Public Cloud ◽  
Infrastructure Investments ◽  
Security Compliance ◽  
Document Stores

In recent years, Cloud Computing has drastically changed IT-Architectures in enterprises throughout various branches and countries. Dynamically scalable capabilities like CPUs, storage space, virtual networks, etc. promise cost savings, as huge initial infrastructure investments are not required anymore. This development shows that Cloud Computing is also a promising technology driver for Big Data, as the storage of unstructured data when no concrete and defined data schemes (variety) can be managed with upcoming NoSQL architectures. However, in order to fully exploit these advantages, the integration of a trustworthy 3rd party public cloud provider is necessary. Thus, challenging questions concerning security, compliance, anonymization, and privacy emerge and are still unsolved. To address these challenges, this work presents, implements and evaluates a security-by-distribution approach for NoSQL document stores that distributes data across various cloud providers such that every provider only gets a small data chunk which is worthless without the others.

A Security-By-Distribution Approach to Manage Big Data in a Federation of Untrustworthy Clouds

2017 ◽  
pp. 92-123 ◽  
Author(s):  
Jens Kohler ◽  
Christian Richard Lorenz ◽  
Markus Gumbel ◽  
Thomas Specht ◽  
Kiril Simov
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Cost Savings ◽  
Cloud Provider ◽  
Small Data ◽  
Storage Space ◽  
Public Cloud ◽  
Infrastructure Investments ◽  
Security Compliance ◽  
Document Stores

In recent years, Cloud Computing has drastically changed IT-Architectures in enterprises throughout various branches and countries. Dynamically scalable capabilities like CPUs, storage space, virtual networks, etc. promise cost savings, as huge initial infrastructure investments are not required anymore. This development shows that Cloud Computing is also a promising technology driver for Big Data, as the storage of unstructured data when no concrete and defined data schemes (variety) can be managed with upcoming NoSQL architectures. However, in order to fully exploit these advantages, the integration of a trustworthy 3rd party public cloud provider is necessary. Thus, challenging questions concerning security, compliance, anonymization, and privacy emerge and are still unsolved. To address these challenges, this work presents, implements and evaluates a security-by-distribution approach for NoSQL document stores that distributes data across various cloud providers such that every provider only gets a small data chunk which is worthless without the others.

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.

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

Fog vs. Cloud Computing Architecture

2021 ◽  
pp. 452-469
Author(s):  
Shweta Kaushik ◽  
Charu Gandhi
Keyword(s):  
Cloud Computing ◽  
New Technology ◽  
Fog Computing ◽  
End Users ◽  
Distributed Data ◽  
Storage Space ◽  
Mobility Support ◽  
Jitter Delay ◽  
Dense Distribution ◽  
Real Time Application

Cloud computing has emerged as a new technology that allows the users to acquire resources at anytime, anywhere by connecting with internet. It provides the options to users for renting of infrastructure, storage space, and services. One service issue that affects the QoS of cloud computing is network latency while dealing with real-time application. In this, the user interacts directly with application but delays in receiving the services, and jitter delay will encourage the user to think about this. In today's world, clients are moving towards the IoT techniques, enabling them to connect all things with internet and get their services from cloud. This advancement requires introduction of new technology termed as “fog computing.” Fog computing is an extension of cloud computing that provides the service at the edge of the network. Its proximity to end users, mobility support, and dense distribution reduces the service latency and improves QoS. This fog model provides the prosperity for advertisement and entertainment and is well suited for distributed data model.

An Overview of Cloud Computing and Deployment of Big Data Analytics in the Cloud

2014 ◽  
pp. 209-215
Author(s):  
Pushpa Mannava
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Analytics ◽  
Evaluation Method ◽  
Big Data Analytics ◽  
Modern Technology ◽  
Data Evaluation ◽  
Storage Space ◽  
Big Data Technology

Big Data is a data evaluation method makes it possible for by recent breakthroughs in details and interactions modern technology. However, big data evaluation requires a massive quantity of calculating resources making fostering costs of big data technology is not inexpensive for lots of small to tool business. In this paper, we detail the benefits as well as obstacles associated with deploying big data analytics through cloud computing. We suggest that cloud computer can support the storage space as well as computing requirements of big data analytics. This paper provides a detailed overview of cloud computing and deployment of big data analytics in the cloud.

scholarly journals A Web-Based Framework for Classification and Integration of News Articles Big Data using Ontology

2019 ◽  
Vol 8 (3) ◽  
pp. 3257-3263
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Semantic Web ◽  
Social Networking ◽  
Social Networking Sites ◽  
Climate Information ◽  
Huge Amount ◽  
Web Based ◽  
Different Sources

Around 2.5 quintillion bytes of data have been created online: out of which most of the data has been generated in the last two years. To generate this huge amount of data from different sources, many devices are being utilized such as sensors to get the data about climate information, social networking sites, banking records, e-commerce records, etc. This data is known as Big Data. It mainly consists of three 3v’s volumes, velocity, and variety. Variety of data discusses about different formats of data originating from various data foundations. Hence, the big data variety’s issue is significant in explaining some genuine challenges. The semantic Web is utilized as an Integrator to join information from different sorts of data foundations like web services, social databases, and spreadsheets and so on and in various formats. The semantic Web is an all-encompassing type of the present web that gives simpler methods to look, reuse, join and offer the data. In this manner, it is along these lines seen as a combiner transversely over different things, information applications, and systems. This paper is an effort to uncover the nature of big data and a brief survey on the use of various semantic web-based methods and tools to add value to today’s big data. In addition, it discusses a case study on performing various machine learning functionalities on news articles and proposes a web-based framework for classification and integration of news articles big data using ontologies.

Fog vs. Cloud Computing Architecture

2019 ◽  
pp. 87-110
Author(s):  
Shweta Kaushik ◽  
Charu Gandhi
Keyword(s):  
Cloud Computing ◽  
New Technology ◽  
Fog Computing ◽  
End Users ◽  
Distributed Data ◽  
Storage Space ◽  
Mobility Support ◽  
Jitter Delay ◽  
Dense Distribution ◽  
Real Time Application

Cloud computing has emerged as a new technology that allows the users to acquire resources at anytime, anywhere by connecting with internet. It provides the options to users for renting of infrastructure, storage space, and services. One service issue that affects the QoS of cloud computing is network latency while dealing with real-time application. In this, the user interacts directly with application but delays in receiving the services, and jitter delay will encourage the user to think about this. In today's world, clients are moving towards the IoT techniques, enabling them to connect all things with internet and get their services from cloud. This advancement requires introduction of new technology termed as “fog computing.” Fog computing is an extension of cloud computing that provides the service at the edge of the network. Its proximity to end users, mobility support, and dense distribution reduces the service latency and improves QoS. This fog model provides the prosperity for advertisement and entertainment and is well suited for distributed data model.

Tracking knowledge evolution in cloud healthcare literature: a cybermetrics study (Preprint)

2019 ◽  
Author(s):  
Dongxiao Gu ◽  
Xuejie Yang ◽  
Shuyuan Deng ◽  
Xiaoyu Wang ◽  
Jiao Wu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Medical Informatics ◽  
Research Work ◽  
Healthcare Research ◽  
Phase Iii ◽  
Knowledge Map ◽  
Medical Field ◽  
Knowledge Evolution ◽  
Word Analysis

BACKGROUND With the continuous development of the Internet and the explosive growth of data, big data technology emerged. The development and application of cloud computing technology provides better storage and analysis of data. The development of cloud healthcare provides a more convenient and effective solution for people’s health. To study the knowledge evolution in the field of cloud healthcare and the research hot topics is becoming one of important issues in medical informatics area. The scholars in medical informatics community need to understand the panorama of the evolution of cloud healthcare research, as well as possible trends in cloud healthcare field as important reference for their future research work. OBJECTIVE Drawing on the cloud healthcare literature, this paper aims at revealing the development and evolution of research themes in cloud healthcare through knowledge map and common word analysis. METHODS A total of 2878 articles in the cloud healthcare literature were retrieved from the Web of Science database. We used cybermetrics to analyze and visualize the keywords in these articles. In particular, we create a knowledge map to show the evolution of cloud healthcare research. We use co-word analysis to reveal the hot topics in cloud healthcare research and their evolution process. RESULTS The evolution and development of cloud healthcare services are shown. And From 2007 to 2009 (Phase I), most scholars applied cloud computing to the medical field mainly to reduce cost; and the technologies used are primarily grid computing and cloud computing. During 2010-2012 (Phase II), scholars began to pay attention to the security of cloud systems. During 2013-2015 (Phase III), the medical informatization created the big data for health services. During 2016-2017 (Phase IV), machine learning and mobile technologies are introduced into the medical field. CONCLUSIONS The research of cloud healthcare has been vigorously developing worldwide, and technologies used in cloud health research are becoming diverged and smart simultaneously. Cloud-based mobile health, cloud-based smart health, as well as the security of cloud health data and systems will be three possible trends in the future development of the cloud healthcare field.

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