scholarly journals From cloud computing to fog computing in Healthcare big data

2018 ◽  
Vol 189 ◽  
pp. 03011
Author(s):  
Babur Hayat Malik ◽  
Faisal Mahmood ◽  
Sohail Shahzad ◽  
Muhammad Bilawal Arif ◽  
Waseem Ur Rehman Khan ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Fog Computing ◽  
Cloud Base ◽  
Healthcare Applications ◽  
Healthcare Data ◽  
Health Report ◽  
Electronic Health ◽  
Design Style ◽  
The Impact

In Healthcare big data, data is originated from various heterogeneous sources. Numerous novel base particular healthcare applications offered to handling source of data from electronic health record (EHR) to medical images. Imaging, Electronic Health Report, technology in light of sensor and numerous different procedures created an immense measure of Healthcare data. Cloud computing development was an excellent paradigm to substantiate big data which incited find of imperceptible examples. Cloud computing is a developing new registering design intended to answer different contending administrations on the Web. Fog Computing is a design style in which arrange segments amongst devices and the cloud execute application-particular rationale. We in this paper investigate, characterize, and talk about various application of cloud and fog computing. We talk about the impact of cloud computing and fog computing on healthcare big data. Cloud base framework for Homediagnosis Service, Fog computing architecture and the justification of moving from cloud to Fog presented comprehensively in this paper.

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.

scholarly journals Mobile Cloud Computing Model and Big Data Analysis for Healthcare Applications

IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 6171-6180 ◽  
Author(s):  
Lo'ai A. Tawalbeh ◽  
Rashid Mehmood ◽  
Elhadj Benkhlifa ◽  
Houbing Song
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Analysis ◽  
Mobile Cloud Computing ◽  
Big Data Analysis ◽  
Mobile Cloud ◽  
Healthcare Applications ◽  
Computing Model

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

scholarly journals Analyzation and Comparison of Cloud Computing and Data Mining Techniques: Big Data and Impact of Blockchain

2021 ◽  
Vol 9 (11) ◽  
pp. 712-721
Author(s):  
Adarsh Bhandari
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Analytics ◽  
Scale Up ◽  
Big Data Analytics ◽  
Multiple Sources ◽  
Huge Data ◽  
Amazon Web Services ◽  
Tools And Techniques ◽  
The Impact

Abstract: With the rapid escalation of data driven solutions, companies are integrating huge data from multiple sources in order to gain fruitful results. To handle this tremendous volume of data we need cloud based architecture to store and manage this data. Cloud computing has emerged as a significant infrastructure that promises to reduce the need for maintaining costly computing facilities by organizations and scale up the products. Even today heavy applications are deployed on cloud and managed specially at AWS eliminating the need for error prone manual operations. This paper demonstrates about certain cloud computing tools and techniques present to handle big data and processes involved while extracting this data till model deployment and also distinction among their usage. It will also demonstrate, how big data analytics and cloud computing will change methods that will later drive the industry. Additionally, a study is presented later in the paper about management of blockchain generated big data on cloud and making analytical decision. Furthermore, the impact of blockchain in cloud computing and big data analytics has been employed in this paper. Keywords: Cloud Computing, Big Data, Amazon Web Services (AWS), Google Cloud Platform (GCP), SaaS, PaaS, IaaS.

scholarly journals Construction of Live Broadcast Training Platform Based on “Cloud Computing” and “Big Data” and “Wireless Communication Technology”

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Zhidong Sun ◽  
Xueqing Li
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Wireless Communication ◽  
Communication Technology ◽  
Security Policy ◽  
High Efficiency ◽  
Rapid Development ◽  
Science And Technology ◽  
Live Broadcast ◽  
The Impact

With the rapid development of information technology, a scientific theory is brought by the rapid progress of science and technology. The advancement of science and technology of the impact on every field, changing the mode of transmission of information, the advent of big data for promotion and dissemination of resources played their part, let more and more people benefit. In the context of cloud computing, big data ushered in another upsurge of development and growth. Given this, the live broadcast training platform, which focuses on enterprise staff training and network education, arises at the right moment. People favor its convenience, real-time performance, and high efficiency. However, the low-value density of big data and cloud computing’s security problem has difficulties constructing a live broadcast training platform. In this paper, the live broadcast training platform’s structure is improved by constructing three modules: the live training module based on cloud computing, the user recommendation module based on big data, and the security policy guarantee module. In addition, to ensure that the trainees can receive training anytime and anywhere, this paper uses wireless communication technology to ensure the quality and speed of all users’ live video sources.

scholarly journals Leveraging Fog Computing for a Secure and Smart Healthcare

2019 ◽  
Vol 8 (2) ◽  
pp. 6117-6122
Keyword(s):  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Fog Computing ◽  
Healthcare Services ◽  
Decision Fusion ◽  
Sensor Data ◽  
Smart Sensors ◽  
Healthcare Applications ◽  
Smart Healthcare ◽  
Iot Devices

From hairbrushes to scales, all devices have sensors embedded in them to collect and communicate data. Smart Healthcare is proving to be an exciting and dynamic area with lots of room for new innovations and the increasing consumer demand for proactive health monitoring devices. Having India poised to spend a lot on healthcare, recent innovations using IoT devices and big data analytics can propel the healthcare industry into the future. Smart healthcare providers are leveraging cloud computing with fog computing to optimize their healthcare services. These smart healthcare applications depend mainly on the raw sensor data collected, aggregated, and analyzed by the smart sensors. Smart sensors these days generate myriad amount of data like text, image, audio, and video that require real-time or batch processing. Aggregating these diverse data from various types of resources remains a dispute till date. To resolve this issue, we have proposed a softwarized infrastructure that integrates cloud computing and fog computing, message brokers, and Tor for supple, safe, viable, and a concealed IoT exploitation for smart healthcare applications and services. Our proposed platform employs machine-to-machine (M2M) messaging, data fusion and decision fusion, and uses rule-based beacons for seamless data management. Our proposed flexBeacon system provides an IoT infrastructure that is nimble, secure, flexible, private, and reasonable. We have also proposed an M2M transceiver and microcontroller for flawless data incorporation of smart healthcare applications and services. Based on the IoT devices’ technical capabilities and resource availability, some systems are capable of making use of homomorphic encryption and zero knowledge proofs. The proposed flexBeacon platform offers seamless management and data aggregation without loss of accuracy. The cost of implementing a softwarized IoT for smart healthcare is also greatly reduced.

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