This paper analyses how Big Data can be stored by Cloud Computing and Fog Computing. 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.
Table of Contents
1 Introduction
2 Background
2.1 Cloud computing
2.2 Big data definitions and characteristic’s in Healthcare
3 Research on big data and cloud computing in Healthcare
3.1 Year of publications
4 Limitations and obstacles of cloud computing
5 Need of fog computing
6 Discussion
6.1 Fog computing features and solutions to different problems
6.2 The implemented fog
6.3 The duty of fog computing
7 Conclusion
Target and Research Scope
This paper explores the integration of Big Data analytics within the healthcare sector, specifically addressing the limitations of cloud computing and proposing fog computing as a more efficient, decentralized architectural solution for time-sensitive medical applications.
- Evolution from traditional cloud computing to fog computing architectures.
- Management and processing of massive healthcare data volumes.
- Challenges of cloud environments including latency and data security.
- Features and benefits of fog computing for IoT-based medical devices.
- Architecture and operational roles of fog computing in healthcare.
Excerpt from the Book
5 Need of fog computing
However, the IT industry giving benefit and solutions of the problems to almost all fields, healthcare sector is also one of them. Still, cloud models is not suitable for critical applications because too has different problems like extreme bandwidth restraints and random response time [12]. Fog Computing is a big alternative solution for the achievement of these requirements. Fog and edge computing in general is an emerging platform that provides computational, storage, and control resources in an intermediate layer between end-user devices and cloud computing datacenters [13].
The word fog computing was at first began by industry as an allegory for the fundamental design thought behind it: fog is anywhere close to the cloud and the ground, wherever the clients' means are found. A word frequently utilized synonymously is edge processing, portraying assignments that are put at the side of the network as opposed to the cloud. According to ETSI's terminology [14] the view of internet service providers, edge is the boundary of the operative's network, similar for example a station based on LTE. According to our interpretation of fog includes these two perspectives. Topology is the core feature of fog computing. Access points, network gateways and routers can be cohesive together with the standard network functions as the resources of the fog computing. There is a unanimity about fog computing, it is not the alternative of the cloud computing, yet rather see it as an impeccable partner or an expansion of it.
Chapter Summary
1 Introduction: Discusses the role of Big Data in healthcare and how cloud computing is utilized for processing large datasets in medical environments.
2 Background: Explains the fundamental concepts of cloud computing and provides definitions and key characteristics of Big Data specifically for the healthcare sector.
3 Research on big data and cloud computing in Healthcare: Examines the yearly statistics of academic publications and the adoption trends of these technologies in the medical field.
4 Limitations and obstacles of cloud computing: Identifies critical issues such as security threats, technical hindrances, data lock-in, and recovery concerns associated with cloud usage.
5 Need of fog computing: Presents fog computing as a solution for critical healthcare applications by reducing latency and improving bandwidth usage.
6 Discussion: Analyzes the features of fog computing and details the architecture, including its role in handling IoT sensors and data processing.
7 Conclusion: Summarizes the necessity of moving towards decentralized computing architectures to optimize healthcare services and privacy.
Keywords
Big Data, Cloud Computing, Fog Computing, Healthcare, Internet of Things, IoT, Data Latency, Edge Computing, Medical Informatics, Network Architecture, Data Security, Data Processing, Sensor Technology, 5G, Biomedical Informatics
Frequently Asked Questions
What is the fundamental focus of this publication?
The paper examines the transition from cloud computing to fog computing models to better handle the growing volume and complexity of Big Data in healthcare.
What are the primary thematic areas covered?
The key themes include Big Data management, cloud infrastructure limitations, the technical necessity for fog computing, and specific architectures for healthcare IoT.
What is the primary research goal?
The goal is to determine how fog computing can bridge the gap in healthcare applications by providing decentralized data processing near the source of data generation.
Which methodology is employed in the work?
The author utilizes a literature review and technical analysis of existing computing architectures to evaluate their efficiency and applicability in the healthcare domain.
What topics are discussed in the main body?
The main body covers the 7 V's of Big Data, the technical obstacles of cloud systems, and the specific functions of fog computing such as reduced latency and energy efficiency.
Which keywords best characterize this research?
Key terms include Big Data, Fog Computing, Cloud Computing, Healthcare, IoT, Latency, and Edge Computing.
Why is standard cloud computing considered insufficient for some healthcare applications?
Cloud models suffer from extreme bandwidth restraints and unpredictable response times, which are unsuitable for critical medical applications requiring immediate data processing.
What is the specific role of fog computing in hospitals?
It acts as an intermediate layer that processes sensitive sensor data at the local edge, ensuring better privacy, reduced latency, and improved energy efficiency for connected devices.
How does the author define the relationship between cloud and fog computing?
The author views fog computing not as a total replacement for the cloud, but as an impeccable partner and a necessary extension for performance-sensitive tasks.
- Arbeit zitieren
- Ajit Singh (Autor:in), 2019, Storage of Big Data. From Cloud Computing to Fog Computing (C2F), München, GRIN Verlag, https://www.hausarbeiten.de/document/489722
