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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Veröffentlicht in:2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity) S. 50 - 53
Hauptverfasser: Zhi Yang, Chunping Zhang, Mu Hu, Feng Lin
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.12.2015
Schlagworte:
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
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Abstract 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.
AbstractList 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.
Author Zhi Yang
Chunping Zhang
Feng Lin
Mu Hu
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  surname: Zhi Yang
  fullname: Zhi Yang
  email: yangzhi1@sgepri.sgcc.com.cn
  organization: State Grid Electr. Power Sci. Res. Inst., Nanjing, China
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  surname: Chunping Zhang
  fullname: Chunping Zhang
  organization: State Grid Electr. Power Sci. Res. Inst., Nanjing, China
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  surname: Mu Hu
  fullname: Mu Hu
  organization: State Grid Electr. Power Sci. Res. Inst., Nanjing, China
– sequence: 4
  surname: Feng Lin
  fullname: Feng Lin
  organization: State Grid Electr. Power Sci. Res. Inst., Nanjing, China
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SubjectTerms 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
Title OPC: A Distributed Computing and Memory Computing-Based Effective Solution of Big Data
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