scholarly journals Analysis and Research on Spatial Data Storage Model Based on Cloud Computing Platform

2017 ◽  
Vol 100 ◽  
pp. 012112 ◽  
Author(s):  
Yong Hu
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Spatial Data ◽  
Storage Model ◽  
Computing Platform ◽  
Model Based ◽  
Cloud Computing Platform

scholarly journals Land Cover Classification Based on Cloud Computing Platform

2020 ◽  
Vol 55 (2) ◽  
Author(s):  
Nghia Viet Nguyen ◽  
Thu Hoai Thi Trinh ◽  
Hoa Thi Pham ◽  
Trang Thu Thi Tran ◽  
Lan Thi Pham ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Land Cover ◽  
Spatial Data ◽  
Google Earth ◽  
Computer Hardware ◽  
Commercial Software ◽  
Computing Platform ◽  
Land Cover Data ◽  
Cloud Computing Platform ◽  
Google Earth Engine

Land cover is a critical factor for climate change and hydrological models. The extraction of land cover data from remote sensing images has been carried out by specialized commercial software. However, the limitations of computer hardware and algorithms of the commercial software are costly and make it take a lot of time, patience, and skills to do the classification. The cloud computing platform Google Earth Engine brought a breakthrough in 2010 for analyzing and processing spatial data. This study applied Object-based Random Forest classification in the Google Earth Engine platform to produce land cover data in 2010 in the Vu Gia - Thu Bon river basin. The classification results showed 7 categories of land cover consisting of plantation forest, natural forest, paddy field, urban residence, rural residence, bare land, and water surface, with an overall accuracy of 73.9% and kappa of 0.70.

A User’s Profile Model for Cloud Computing Service

2013 ◽  
Vol 774-776 ◽  
pp. 1729-1733 ◽  
Author(s):  
Wu Bin Ma ◽  
Ming Xin Liu ◽  
Su Deng ◽  
Hong Bin Huang
Keyword(s):  
Cloud Computing ◽  
User Models ◽  
Profile Model ◽  
Computing Platform ◽  
Model Based ◽  
Cloud Computing Service ◽  
Cloud Computing Platform

Personalization of model-based cloud computing platform based on specialized user models has become more important in order to preserve the effectiveness of their service as the amount of available content increases. In this paper, a users profile model is imported to the cloud computing. We propose a method of modeling users profile for cloud computing, and establish a simple users profile. At last, we use this model in the Google App Engine for searching some service to prove that importing the users profile model is useful and efficient for cloud computing service.

Massive 3D spatial data storage model based on file system

2010 ◽  
Author(s):  
Ka Sun ◽  
Chonglong Wu ◽  
Gang Liu ◽  
Yingying Li ◽  
Pinqian Wang
Keyword(s):  
Data Storage ◽  
Spatial Data ◽  
File System ◽  
Storage Model ◽  
Model Based

An IoT-Oriented Data Storage Framework in Cloud Computing Platform

2014 ◽  
Vol 10 (2) ◽  
pp. 1443-1451 ◽  
Author(s):  
Lihong Jiang ◽  
Li Da Xu ◽  
Hongming Cai ◽  
Zuhai Jiang ◽  
Fenglin Bu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Computing Platform ◽  
Cloud Computing Platform

Research of Smart Meter Massive Data Storage Based on Cloud Computing Platform

2013 ◽  
Vol 341-342 ◽  
pp. 1434-1438
Author(s):  
Weng Ting Li ◽  
Yan Zheng ◽  
Shao Bo Liu ◽  
Zhao Zhi Long ◽  
Zhi Cheng Li
Keyword(s):  
Cloud Computing ◽  
Smart Grid ◽  
Data Storage ◽  
Massive Data ◽  
Smart Meter ◽  
Smart Meters ◽  
Computing Platform ◽  
Cloud Computing Platform ◽  
Distributed Computing Platform ◽  
Grid Operation

With the comprehensive construction of the smart grid, the smart grid operation control and interactive service system will be initially formed. The smart terminal of smart grid are smart meters, and they produce a large number of various data all the time. That how to most effectively manage these massive data storage is an important research point for improving the intelligence service. This paper studies the smart meter massive data storage management based on cloud computing platform. The Hadoop distributed computing platform for smart meter massive data management is reliable, efficient, scalable storage.

A P2P Resource Management Model Based on Cloud Computing

2014 ◽  
Vol 989-994 ◽  
pp. 1930-1933
Author(s):  
Yang Lu ◽  
Guang Feng Liu
Keyword(s):  
Cloud Computing ◽  
Resource Management ◽  
Cloud Layer ◽  
Management Model ◽  
Cloud Systems ◽  
Computing Platform ◽  
The Core ◽  
Model Based ◽  
Cloud Computing Platform ◽  
And Storage

The technology of cloud computing has become a hot issue of research in the service of network in recent years. Cloud computing platform provide computing and storage services to customers. And it has been widely applied in e-business, e-education and etc.. While Cloud systems are usually hosted in large datacenters which may become a bottleneck to the system. In this paper we describe the design of a double-layer P2P model based on cloud computing. In the model, user nodes grouped into clusters form the Extended Cloud layer, and transfer file to each other without participation of the Core Cloud layer. The new model has better scalability and efficiency.

Design of Distribute Monitoring Platform Base on Cloud Computing

2014 ◽  
Vol 687-691 ◽  
pp. 1076-1079
Author(s):  
Qi Sun ◽  
Hui Yan Zhao
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Mass Measurement ◽  
Measurement Data ◽  
Distributed Network ◽  
Computing Platform ◽  
Analytical Processing ◽  
Cloud Computing Platform ◽  
Measurement Infrastructure ◽  
Processing Mechanism

Based on cloud computing distributed network measurement system compared to traditional measurement infrastructure, the use of cloud computing platform measurement data stored in massive large virtual resource pool to ensure the reliability of data storage and scalability, re-use cloud computing platform parallel processing mechanism, the mass measurement data for fast, concurrent analytical processing and data mining. Measuring probe supports a variety of different measurement algorithms deployed to support a variety of data acquisition formats, in the measurement method provides a congestion response policies and load balancing strategies.

A Cloud Computing Architectural Model Based on Virtual Machine Pool

2013 ◽  
Vol 798-799 ◽  
pp. 668-671
Author(s):  
Wu Xue Jiang ◽  
Hui Hu ◽  
Peng Fei Yin ◽  
Jian Feng Luo
Keyword(s):  
Cloud Computing ◽  
Data Center ◽  
Practice Research ◽  
Application Development ◽  
Architecture Model ◽  
Computing Platform ◽  
Computing Model ◽  
Model Based ◽  
New Type ◽  
Cloud Computing Platform

Cloud computing is a new-type of computing model. This paper deeply expounded the key technology of virtualization and cloud computing through theoretical analysis and practice research on cloud computing and its architecture. Then, it proposed a common cloud computing architecture model based on virtual environment, which consisted of layers of data center, cloud file system, computing model, data management, and application development. In addition, it realized a cloud computing platform based on Hadoop.

A Comprehensive Security Strategy Applying to the Total Life Cycle of Cloud Computing Data Center

2014 ◽  
Vol 556-562 ◽  
pp. 6259-6261
Author(s):  
Zhao Yang Dong ◽  
Lin Zhang
Keyword(s):  
Cloud Computing ◽  
Life Cycle ◽  
Data Storage ◽  
Data Center ◽  
Cloud Service ◽  
Security Measures ◽  
Security Issues ◽  
Computing Platform ◽  
Authentication And Authorization ◽  
Cloud Computing Platform

Aiming at the security issues of cloud computing data center, the systematic security construction architecture of cloud computing data center is proposed. By surrounding the key aspects of security construction, such as infrastructure security, virtual security, cloud authentication and authorization, data isolation and protection, cloud platform and cloud service security, security operation maintenance, cloud computing platform migration, and disaster recovery backup, the security architecture constructs a multi-level, multi-angle tridimensional defense system in depth. It ensures the life cycle security for resource services of the cloud computing data center. Many key problems are further discussed in detail, such as the problem of data storage security, security domain isolation, cloud computing platform tenants accessing, and terminal accessing. This paper provides reference for the security construction of cloud computing data center, and gives guide to the implementation of the relevant security measures.

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