OPC: A Distributed Computing and Memory Computing-Based Effective Solution of Big Data

The Big Data computing is one of hot spots of the internet of things and cloud computing. How to compute efficiently on the Big Data is the key of improving performance. By means of distributed computing or memory computing, many companies and institutions provide some technologies and produces. But...

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Bibliographic Details
Published in:	2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity) pp. 50 - 53
Main Authors:	Zhi Yang, Chunping Zhang, Mu Hu, Feng Lin
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.12.2015
Subjects:	Architecture of Objectification Parallel Computing Big data Computers Distributed computing Distributed Memory Computing Memory management Objectification Parallel Computing Parallel Computing Parallel processing Real-time systems
Online Access:	Get full text
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Summary:	The Big Data computing is one of hot spots of the internet of things and cloud computing. How to compute efficiently on the Big Data is the key of improving performance. By means of distributed computing or memory computing, many companies and institutions provide some technologies and produces. But they are invalid in the scene in which there are real-time demands in the low-configure cluster. To deal with the problem, this paper provides a distributed computing and memory computing-based effective solution (Objectification Parallel Computing, OPC). In the solution, the data can be formatted into object. Then the objects are distributed stored in the computer memories and parallel compute to complete tasks. The OPC is applied to the Electric Asset Quality Supervision Manage System (EAQSMS) of State Grid of China, the result shows that with PCs the system is efficiently available, reliable, and flexible expansible.
DOI:	10.1109/SmartCity.2015.46