scholarly journals The Design of Cloud Computing Platform for Massive Data Processing of Distributed Photovoltaic Power

2015 ◽  
Author(s):  
Bing Jiang ◽  
Kun Huang
Keyword(s):  
Cloud Computing ◽  
Data Processing ◽  
Massive Data ◽  
Computing Platform ◽  
Photovoltaic Power ◽  
Cloud Computing Platform ◽  
Massive Data Processing

Cloud Data Management Based on Cloud Computing Technology

2014 ◽  
Vol 543-547 ◽  
pp. 3573-3576
Author(s):  
Yuan Jun Zou
Keyword(s):  
Cloud Computing ◽  
Parallel Computing ◽  
Data Processing ◽  
Development Planning ◽  
Computer Data ◽  
Cloud Data ◽  
Computing Platform ◽  
Convergence Error ◽  
Cloud Computing Platform ◽  
Cloud Data Processing

Cloud computing, networking and other high-end computer data processing technology are the important contents of eleven-five development planning in China. They have developed rapidly in recent years in the field of engineering. In this paper, we combine parallel computing with the collaborative simulation principle, design a cloud computing platform, establish the mathematical model of cloud data processing and parallel computing algorithm, and verify the applicability of algorithm through the numerical simulation. Through numerical calculation, cloud computing platform can be divided into complex grids, and the transmission speed is fast, which is eight times than the finite difference method. The mesh is meticulous, which reaches millions. Convergence error is minimum, only 0.001. The calculation accuracy is up to 98.36%.

scholarly journals Research and Application of Massive Data Processing in Oil Services

2012 ◽  
Vol 6-7 ◽  
pp. 1036-1040
Author(s):  
Bao An Li
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Data Processing ◽  
Rapid Growth ◽  
Massive Data ◽  
Oil Drilling ◽  
Data Problem ◽  
Traditional Industry ◽  
Massive Data Processing

Big data problem has caused widespread concern from industry to academia in recent years. As the amount of data produced by various industries and sectors of rapid growth, increasing demands on data processing and analysis capabilities, how to face the challenges of data, discover new opportunities, the issue has received wide attention. As a traditional industry, the oil drilling or refinery enterprise is facing the operational status of the system to produce large amounts of data. This text introduced an approach to massive data processing for oil enterprise based on cloud computing and Internet of Things.

A Novel Approach in Improving I/O Performance of Small Meteorological Files on HDFS

2011 ◽  
Vol 117-119 ◽  
pp. 1759-1765 ◽  
Author(s):  
Sheng Jun Xue ◽  
Wu Bin Pan ◽  
Wei Fang
Keyword(s):  
Cloud Computing ◽  
Data Processing ◽  
Meteorological Data ◽  
Storage Space ◽  
Master Node ◽  
Reading And Writing ◽  
Computing Platform ◽  
Novel Approach ◽  
Computing Performance ◽  
Cloud Computing Platform

With the cloud computing is becoming mature, many of its characteristics for meteorological data processing is extremely important. Since HDFS is designed for reading and writing large files, it’s difficult to be taken advantage of small meteorological files. In this paper, an improved approach on HDFS is proposed for small meteorological files, small files are to be merged, indexed, and blocks are compressed, the pressure of memory on master node occupied by metadata is relieved, the speed of reading and writing small files is increased, read speed is increased by 50%, and write speed is up to 3-4 times of the original, saving about 2/3 of storage space and computing performance has also been improved. Thus, meteorological data processing can make use of cloud computing platform more closely.

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.

Research of Cloud Computing in Management Information System

2013 ◽  
Vol 655-657 ◽  
pp. 1826-1829
Author(s):  
Zheng Xing Xiao
Keyword(s):  
Cloud Computing ◽  
Information System ◽  
Management Information System ◽  
Massive Data ◽  
Management Information ◽  
Computing Platform ◽  
Complex Functions ◽  
Cloud Computing Platform ◽  
Diverse Data

characteristics of current MIS System are massive data、diverse data and complex functions. This kind of System requires higher requirement to Storage and Computing. This paper proposes a way to resolve it by build cloud computing platform by making full use of large number of idle computers.

Design and Implementation of Massive Data Retrieving Based on Cloud Computing Platform

2013 ◽  
Vol 303-306 ◽  
pp. 2235-2240 ◽  
Author(s):  
Wei Xiao ◽  
Chun Lei Ji ◽  
Jian Dun Li
Keyword(s):  
Cloud Computing ◽  
Massive Data ◽  
Computing Platform ◽  
Design And Implementation ◽  
Computing Paradigm ◽  
Hybrid Solution ◽  
Great Availability ◽  
Cloud Computing Platform ◽  
Computing Framework ◽  
Low Efficiency

Considering the low efficiency of massive data retrieving in traditional parallel processing, by taking advantage of the great availability of cloud computing paradigm, we propose a hybrid solution based on Map-Reduce model and distributed computing framework--Spark. Moreover, we design and implement this solution in our lab. The results show that the solution can effectively improve the performance of massive data retrieving.

Optimization and Management in Order to Drive Targeted Networking Memory Database

2015 ◽  
Vol 727-728 ◽  
pp. 965-968
Author(s):  
Ji Liu
Keyword(s):  
Cloud Computing ◽  
Wireless Communication ◽  
Data Processing ◽  
Real Time ◽  
System Architecture ◽  
Large Data ◽  
Processing Efficiency ◽  
Computing Platform ◽  
Cloud Computing Platform ◽  
Vehicle Networking

In today's vehicle networking system architecture is mainly composed of four parts: sensor networks, wireless communication networks, cloud computing platforms and vehicle terminal. Wireless sensor network is responsible for the front of the real-time collection of traffic information, a wireless communication network to send information to the backend of the cloud computing platform, cloud computing platform to handle a large number of vehicles to collect real-time information from the front, and finally sends the information to the end user. In this thesis, this car networking research background, analyze vehicle networking system architecture consisting of performance indicators for each part of the system recognize cloud platform for large data processing efficiency as well as room for improvement. Then put forward the traditional computing platform I / O disk database with in-memory database to replace the cloud to enhance cloud computing platform for large data processing efficiency.

Research and Practice of Cloud Computing Based on Hadoop

2014 ◽  
Vol 644-650 ◽  
pp. 3387-3389
Author(s):  
An Sheng Lu ◽  
Jian Jiang Cai ◽  
Wei Jin ◽  
Lu Wang
Keyword(s):  
Cloud Computing ◽  
Calculation Model ◽  
Distributed File System ◽  
Massive Data ◽  
Operating Environment ◽  
Computing Platform ◽  
Computing Model ◽  
Hadoop Distributed File System ◽  
Hadoop Platform ◽  
Cloud Computing Platform

Hadoop is a distributed parallel processing of massive data computing platform. It is currently the most widely used cloud computing platform. This paper analyses and studies the Hadoop distributed file system HDFS and the calculation model of MapReduce on Hadoop platform and the cloud computing model that is based on Hadoop, the paper introduces the process of building cloud computing platform, Hadoop, operating environment, and proposing the implementation.

Data Processing Platform of Cloud Computing and Its Performance Analysis Based on Photoelectric Hybrid Interconnection Architecture

2020 ◽  
Vol 15 (6) ◽  
pp. 743-752
Author(s):  
Zhimin Ren
Keyword(s):  
Cloud Computing ◽  
Topology Optimization ◽  
Data Processing ◽  
Optical Interconnection ◽  
Circuit Switching ◽  
Computing Platform ◽  
Optical Circuit ◽  
Optical Circuit Switching ◽  
Cloud Computing Platform ◽  
Processing Platform

Data processing platform is the core support platform of cloud computing. The use of electric interconnection architecture will increase the complexity of network topology, while optical interconnection architecture is ideal, so cloud computing platform based on optical interconnection has become a research hotspot. The distributed optical interconnection architecture of cloud computing data processing platform is focused on. Combining the hybrid mechanism of optical circuit switching and electric packet switching, it can meet a variety of traffic requirements. Meanwhile, it improves the switching mechanism, communication strategy, and router structure. Moreover, considering that the hybrid optoelectronic interconnection architecture can improve the network delay and throughput, but there is still a problem of network consumption. Combined with the network characteristics of the data processing platform (wireless mesh structure) of cloud computing, the network topology algorithm is studied, and the relationship between the topology and the maximum number of allocable channels is analyzed. Furthermore, the equation of topological reliability calculation is defined, and the optimization model of topological design is proposed, according to which the data processing platform of cloud computing is further optimized under the photoelectric hybrid interconnection architecture. During the experiment, before topology optimization, by changing the message length, it is found that adding optical circuit switching can help achieving large capacity and new type of transmission, and can effectively reduce the time delay. After topology optimization structure is adopted, the photoelectric hybrid-data processing platform of cloud computing without topology optimization is compared. It is found that under different reliability constraints, the throughput and end-to-end delay of the network are significantly improved, which proves that the data processing platform of cloud computing based on the photoelectric hybrid interconnection architecture is a feasible cloud computing platform.

Sign in / Sign up

Export Citation Format

Share Document