scholarly journals On Study of Application of Big Data and Cloud Computing Technology in Smart Campus

2017 ◽  
Vol 100 ◽  
pp. 012026 ◽  
Author(s):  
Zijiao Tang
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Computing Technology ◽  
Smart Campus

scholarly journals The Construction and Thinking of Cloud Computing and Big Data Technology in Smart Campus

2019 ◽  
Vol 3 (2) ◽  
pp. 152
Author(s):  
Xianglan Wu
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Storage ◽  
Information Technologies ◽  
Rapid Development ◽  
Smart Campus ◽  
Huge Data ◽  
New Information ◽  
Big Data Technology

<p>In today's society, the rise of the Internet and rapid development make every day produce a huge amount of data. Therefore, the traditional data processing mode and data storage can not be fully analyzed and mined these data. More and more new information technologies (such as cloud computing, virtualization and big data, etc.) have emerged and been applied, the network has turned from informationization to intelligence, and campus construction has ushered in the stage of smart campus construction.The construction of intelligent campus refers to big data and cloud computing technology, which improves the informatization service quality of colleges and universities by integrating, storing and mining huge data.</p>

Trends and Technologies in Big Data Processing

2020 ◽  
pp. 17-42
Author(s):  
Amitava Choudhury ◽  
Kalpana Rangra
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Data Processing ◽  
Real Time ◽  
Computing Technology ◽  
Time Data ◽  
Big Data Processing ◽  
Real Time Data ◽  
Real Time Data Processing

Data type and amount in human society is growing at an amazing speed, which is caused by emerging new services such as cloud computing, internet of things, and location-based services. The era of big data has arrived. As data has been a fundamental resource, how to manage and utilize big data better has attracted much attention. Especially with the development of the internet of things, how to process a large amount of real-time data has become a great challenge in research and applications. Recently, cloud computing technology has attracted much attention to high performance, but how to use cloud computing technology for large-scale real-time data processing has not been studied. In this chapter, various big data processing techniques are discussed.

Research of Association Rules Algorithm Based on Matrix under Cloud Computing

2014 ◽  
Vol 568-570 ◽  
pp. 798-801
Author(s):  
Ye Qing Xiong ◽  
Shu Dong Zhang
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Big Data ◽  
Association Rules ◽  
Apriori Algorithm ◽  
Computing Technology ◽  
Binary Matrix ◽  
Transaction Data ◽  
Big Data Mining ◽  
Parallel Mining

It occurs time and space performance bottlenecks when traditional association rules algorithms are used to big data mining. This paper proposes a parallel algorithm based on matrix under cloud computing to improve Apriori algorithm. The algorithm uses binary matrix to store transaction data, uses matrix "and" operation to replace the connection between itemsets and combines cloud computing technology to implement the parallel mining for frequent itemsets. Under different conditions, the simulation shows it improves the efficiency, solves the performance bottleneck problem and can be widely used in big data mining with strong scalability and stability.

Examining Data Lake Design Principle for Cloud Computing Technology and IoT

2018 ◽  
pp. 228-250
Author(s):  
Deepak Saini ◽  
Jasmine Saini
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Design Principle ◽  
Business Value ◽  
Computing Technology ◽  
Multiple Systems ◽  
Good Design ◽  
The World ◽  
Data Files ◽  
Cloud Servers

In the Cloud-based IoT systems, the major issue is handling the data because IoT will deliver an abundance of data to the Cloud for computing. In this situation, the cloud servers will compute the big data and try to identify the relevant data and give decisions accordingly. In the world of big data, it is a herculean task to manage inflow, storage, and exploration of millions of data files and the volume of information coming from multiple systems. The growth of this information calls for good design principles so that it can leverage the different big data tools available in the market today. From the information consumption standpoint, business users are exploring new insights from the big data that can uncover potential business value. Data lake is a technology framework that helps to solve this big data challenge.

scholarly journals Towards a Simulator for Green Smart Campus Systems

2020 ◽  
Author(s):  
Priscila Moraes ◽  
Flávia Pisani ◽  
Juliana Borin
Keyword(s):  
Economic Growth ◽  
Sustainable Development ◽  
Cloud Computing ◽  
Big Data ◽  
Social Inclusion ◽  
Smart Campus ◽  
2030 Agenda ◽  
Information And Communication ◽  
Sustainability Challenges ◽  
The University

The 2030 Agenda for Sustainable Development aims to foster environmental protection, inclusive economic growth, and social inclusion. Universities are called to join this global effort and are expected not only to contribute with solutions for the sustainability challenges but also provide sustainable campi. Given this scenario, the main contributions of this paper are threefold: i) to illustrate how universities could contribute with the 2030 Agenda through smart campus solutions based on technologies such as Internet of Things, Big Data, and Cloud Computing; ii) to propose a framework to automatically collect data to generate and manage sustainability indicators in the university; and iii) to propose a simulator for green smart campus system which allows an adequate estimate of the required information and communication infrastructure.

Enterprise financial management information system based on cloud computing in big data environment

2020 ◽  
Vol 39 (4) ◽  
pp. 5223-5232
Author(s):  
Xuanjun Chen ◽  
N Metawa
Keyword(s):  
Cloud Computing ◽  
Information System ◽  
Big Data ◽  
Management Information System ◽  
Financial Management ◽  
Shared Services ◽  
Computing Technology ◽  
Management Information ◽  
Management Concept ◽  
Data Environment

Cloud computing technology has the characteristics of low investment costs, strong reliability, flexible expansion, and on-demand services, which can greatly reduce the application threshold of enterprise financial informatization construction, improve the return on investment of informationization, and flexibly adapt to the needs of different stages of business. To solve the problem of enterprise financial management information system based on cloud computing in big data environment. This article proposes the management concept of “business-driven value” as an expense management system. Through the investigation of the company in this article, after 9 years of construction, the number of property in each subsidiary has dropped from an average of 23 people per company to 3.5 people per subsidiary before. Reduced by about 84.7%. Contracted human capital for the company. Compared with the 23 billion yuan in 2010, after the implementation of financial shared services, after 9 years of development, it has now reached 68.55 billion yuan, nearly three times more than before.

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