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An Investment Defined Transaction Processing Towards Temporal and Spatial Optimization with Collaborative Storage and Computation Adaptation

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Intelligent Data Engineering and Automated Learning – IDEAL 2017 (IDEAL 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10585))

Abstract

Transaction processing technology is the key technology of reporting information consistency and reliability, and determines whether web services can be applied to e-commerce. We propose an investment defined transaction processing approach towards temporal and spatial optimization with collaborative storage and computation adaptation approach aiming at satisfying requirements of different users according to their investment. We studies resource modelling, resource processing, processing optimization and resource management and puts forward a three-tier architecture consisting of Data Graph, Information Graph and Knowledge Graph.

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Acknowledgment

This paper is supported by NSFC under Grant (No. 61363007, No. 61662021, No. 61661019), NSF of Hainan No. ZDYF2017128.

Author information

Authors and Affiliations

  1. College of Information Science and Technology, State Key Laboratory of Marine Resource Utilization in the South China Sea, Hainan University, Haikou, China

    Yucong Duan, Lixu Shao & Donghai Zhu

  2. School of Information Engineering, Yangzhou University, Yangzhou, China

    Xiaobing Sun

  3. School of Computer and Information, Shanghai Polytechnic University, Shanghai, China

    Xiaoxian Yang

  4. Faculty of Information Sciences and Engineering, MSU, Shah Alam, Malaysia

    Abdelrahman Osman Elfaki

Authors
  1. Yucong Duan
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  2. Lixu Shao
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  3. Xiaobing Sun
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  4. Donghai Zhu
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  5. Xiaoxian Yang
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  6. Abdelrahman Osman Elfaki
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Corresponding author

Correspondence to Yucong Duan .

Editor information

Editors and Affiliations

  1. University of Manchester, Manchester, United Kingdom

    Hujun Yin

  2. School of Electronic and Electrical Engineering, Nanjing University, Nanjiing, China

    Yang Gao

  3. Nanjing University of Aeronautics and Astronautics, Nanjing, China

    Songcan Chen

  4. Guilin University of Electronic Technology, Guilin, China

    Yimin Wen

  5. Guilin University of Electronic Technology, Guilin, China

    Guoyong Cai

  6. Guilin University of Electronic Technology, Guilin, China

    Tianlong Gu

  7. Beijing University of Posts and Telecommunications, Beijing, China

    Junping Du

  8. University of Seville, Seville, Spain

    Antonio J. Tallón-Ballesteros

  9. Southeast University, Nanjing, China

    Minling Zhang

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Duan, Y., Shao, L., Sun, X., Zhu, D., Yang, X., Elfaki, A.O. (2017). An Investment Defined Transaction Processing Towards Temporal and Spatial Optimization with Collaborative Storage and Computation Adaptation. In: Yin, H., et al. Intelligent Data Engineering and Automated Learning – IDEAL 2017. IDEAL 2017. Lecture Notes in Computer Science(), vol 10585. Springer, Cham. https://doi.org/10.1007/978-3-319-68935-7_49

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  • DOI: https://doi.org/10.1007/978-3-319-68935-7_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68934-0

  • Online ISBN: 978-3-319-68935-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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