“21-st Digital Maritime Silk Road” Based on Big Data and Cloud Computing Technology Facing Opportunities and Challenges–From Digital Trade Perspective

2020 ◽  
pp. 446-451
Author(s):  
Shengnan Zheng
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Silk Road ◽  
Computing Technology ◽  
Maritime Silk Road ◽  
Trade Perspective

Modelling the competitiveness of the ports along the Maritime Silk Road with big data

2018 ◽  
Vol 118 ◽  
pp. 852-867 ◽  
Author(s):  
Peng Peng ◽  
Yu Yang ◽  
Feng Lu ◽  
Shifen Cheng ◽  
Naixia Mou ◽  
...  
Keyword(s):  
Big Data ◽  
Silk Road ◽  
Maritime Silk Road

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 Innovation Report of Big Data on Marine Forecast on the North Line of Maritime Silk Road

2020 ◽  
Vol 213 ◽  
pp. 03023
Author(s):  
Bo Lin
Keyword(s):  
Big Data ◽  
Silk Road ◽  
Observation System ◽  
Data Infrastructure ◽  
Business Innovation ◽  
The North ◽  
Data Application ◽  
Maritime Silk Road ◽  
Big Data Application ◽  
To Come

Since the first Arctic expedition in China in 1999, the National Marine Environment Forecasting Center of China has undertaken safety guarantee tasks for the 9 batches of Arctic scientific expedition ships (teams) and 26 merchant ships to come and back the North Line of Maritime Silk Road in China. This paper summarized their successful experience and innovation achievements in big data application, emphatically introduced the innovation of big data infrastructure construction of Maritime Silk Road marine forecasting, that is, the establishment of independent marine observation system, the exploration of international cooperation mode of marine observation, as well as the participation in global regional observation plans. Besides, marine prediction business innovation, safety guarantee service innovation, and supercomputing technology innovation were included in the scientific and technological business innovation. Moreover, the innovation achievements include aspects of polar marine prediction big data, guarantee technology big data and supercomputing. Finally, the construction and development prospect on the North Line of Maritime Silk Road were briefly prospected.

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