Storage of Big Data. From Cloud Computing to Fog Computing (C2F)

Academic Paper, 2019

17 Pages, Grade: 8.67



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


Abstract. 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.

1 Introduction

Healthcare plans to retain and enhance human health by means of analysis, treatment and disease counteractive action. As inspired by patient care, inspecting, organization and necessities to comply with principles and controls, it generates enormous measures of information - Big Data consistently BD can possibly Support numerous medicinal and healthcare tasks, including clinical choice help, disease surveillance and population health management. Cloud computing can diminish the expenses of computerization and framework support, then enhancing operational effectiveness and client access. A tremendous amount of data has generated, by the Innovations in the OMICS-fields (proteomics, genomics) for processing and storing purpose. Different types of data are collected for different purposes and then converted in digital form.

To achieve these requirements cloud computing is a good solution. Clouds guarantee points of attention in unique assets like computing power or capacity edges, pervasive approach to resources whenever from anywhere, and high flexibility and versatility of resources by the different benefits adaptation of cloud computing is increasing in many business domains.

Big Data in healthcare services is overpowering a result of its volume along with in view of the decent variety of information writes and the speed on which data must be 3G/4G/5G are the technologies used in the cloud and the modest mobile devices. Another current innovation is cloud computing (see Fig. 1) by using that you can access information at any time and different organizations could be used this as well as individual users for the betterment in performance. NIST define the concept of cloud computing as: a paradigm for emboldening extensive, helpful, on-request arrange approach to a common pool of configurable managing assets can be provisioned and discharged quickly with minor administration exertion or specialist association collaboration [1].

Abbildung in dieser Leseprobe nicht enthalten

Fig. 1. Cloud computing concept.[2]

Clouds promise advantages in dynamic resources like computing power or storage capacities, ubiquitous access to resources at any time from any place, and high flexibility and scalability of resources [3].Because of the heterogeneous sources and huge volume, healthcare data is more complex. As big data is a new pattern, same way it’s new in the field of biomedical informatics. To achieve IT need in true sense in healthcare sector cloud computing is a great roadmap. It is not possible for cloud to give the sensing facility and many devices use sensor technology, those are utilizing in many hospitals. Another issue is that, due to data confidentiality, some rules do not give permission to store the data outside the boundary of that hospital. Fog computing plays the role of bridge to overcome the gap for the sensors application in hospitals. A term often used synonymously is edge computing, describing tasks that are placed at the edge of the network in contrast to the cloud [4].

The literature covers the topic of cloud computing in healthcare from a variety of viewpoints. Further, we need to recognize areas those are facing problems inside the healthcare field where cloud computing applications have for the most part been conferred. The paper is containing the following different parts. In Sec-I, presently we will show the model of Big Data, Cloud computing and list the key characteristics. In Sect-II, we discuss some of the drifts and obstacles of cloud computing in healthcare. In Sect. III, we show the yearly distribution of publications according to MEDLINE Results. In Sect. IV we provide a big picture of the fog computing, its characteristics and how is it overcome the issues in the healthcare sector. In Sect. V discussion regarding the fog architecture for healthcare and its services. We determine with an indication of the existing condition of study, and also determine outline for further research for employing fog computing in healthcare.

2 Background

2.1 Cloud computing

Cloud computing could be a quickly developing advancement that has developed itself inside its following time industry. Effective design of cloud services can execute extensive computing tasks and period orchestrates of IT works from storing and calculation to database and function facilities. The new cloud computing technology promises to satisfy the IT needs in a more favourable way [5]. Different companies use cloud computing to process and analyse huge volume of datasets. Furthermore, cloud facility suppliers have started to combine frameworks for similar processing of data in their packages to support cloud resources for the access of user. Cloud computing model allows appropriate network access too many aligned computing sources that can be speedily provisioned and freed with least managing effort. NIST cloud framework also defines five key attributes, three service models, and four deployment models [6]. Cloud computing model based on of PaaS, SaaS, and IaaS.

2.2 Big data definitions and characteristic’s in Healthcare

Since being authored in 1997 by NASA specialists, the term BD has been reclassified over and over amid the years [7]. According to a 2013 Commonwealth of Australia report, about 90% of data today was created in the last 2 years [8]. Every day, all kinds of data sources generate 2.5 quintillion bytes of data [9]. Big data is recognized as a multidisciplinary information processing system. Areas of business, government, media, and in particular healthcare, are increasingly incorporating big data into information processing systems [8].

- “Data of a very large size, typically to the extent that its manipulation and management present significant logistical challenges; also, the branch of computing involving such data” (Oxford English Dictionary)

Most primary data is created and stored by health services providers, including general practitioner doctors, specialists and surgeons, public and private hospitals and clinics [10].The attributes of BD can be combined by 7 Vs [7], which are outlined in Fig.2.

i. Volume: Huge amount of data is already gathered from millions of patients and stored electronically to increase the efficiency of healthcare services and provide many research opportunities. Storage is a big problem.
ii. Variety: Because of heterogeneity in data sources, it is difficult to decide a specific pattern of data. It includes semi structured or unstructured data in healthcare sector. For example, text messages, online games, blogs, and social media generate different types of unstructured data through mobile devices and sensors [8].
iii. Velocity: The term Velocity alludes to the speed with which information is created. The age of state-of-the-art comes about because of ongoing or close constant preparing is vital, for instance, in clinical choice help, for having the capacity to settle on the correct choices quickly [11]
iv. Veracity: Data veracity concerns with safety of the patient, but at the same time there is a threat of less quality, wrong and unstructured data [5].
v. Variability: Variability refers to interpretable factor the data. For instance, advanced calculations are fundamental with a specific end goal to deduct the right significance of web-based social networking remarks.
vi. Visualization: Visualization alludes to the meaningfulness about the data introduction, which needs various geographical and worldly limitations and connections among them.
vii. Value: Value denotes to the prospect of making new information and financial incentive by misusing the information.

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Fig 2. Big data characteristics [7].

3 Research on big data and cloud computing in Healthcare

3.1 Year of publications

This section the shows the yearly statistics about the publications according to the MEDLINE results. Figure 3 depicts that publications on big data and cloud computing in healthcare sector. It also tells the yearly distribution of articles about the topic. Management of big data and cloud computing architecture devices are expensive ones and they may take long time for adoption. Moreover, these are latest technologies that’s why they require some time for the proper working and become the part of the existing system.

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Fig.3. Yearly distribution of published articles[8].

4 Limitations and obstacles of cloud computing

Security threats: Organizations are having sensitive data that is more confidential. Customers have to trust on the cloud service provider for the security of their data only.

Technical Hindrance: In cloud environment, data is on cloud instead of local system. That’s why, there is essential requirement of high speed internet. Because if high speed connection is not available then there must be technical issue especially in bulk uploading.

Data lock-in: The absence of standard APIs confines the relocation of utilizations and administrations between clouds. With the ascent of cloud, the issues of Data movability, movement and seller secure circumstance will increment.


Excerpt out of 17 pages


Storage of Big Data. From Cloud Computing to Fog Computing (C2F)
Master Of Computer Application
Catalog Number
ISBN (eBook)
Big Data, Cloud Computing, Fog Computing, Healthcare Use Case
Quote paper
Ajit Singh (Author), 2019, Storage of Big Data. From Cloud Computing to Fog Computing (C2F), Munich, GRIN Verlag,


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