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Parallel Bidirectional Shortest Path Computation in Graphs Using Relational Database Management Systems (RDBMSs)

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Advances in Computer Science and Ubiquitous Computing (CUTE 2018, CSA 2018)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 536))

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Abstract

Graph data structures are widely used in computer science fields such as biometric information, navigational systems etc. Recently there has been significant research into quickly calculating the shortest path of a graph using the latest databases such as Neo4j, Spark, etc. Alternatively, the Frontier-Expand-Merge operator (FEM) provides a method to find the shortest path using only SQL in RDBMSs. However, the FEM utilizes sequential searching and iterative aggregate functions to find the shortest path. We propose parallel shortest path searching and table indexing as substitution for the aggregate function. To prove the effectiveness of this approach, we compared each method using experimentation and could demonstrate an improvement of up to 80% in processing speed with our proposal.

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References

  1. Neo4j. https://neo4j.com/

  2. Apache Spark. https://spark.apache.org/

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Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2017R1C1B1003600) and Institute for Information & Communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (No. R0113-15-0005, Development of a Unified Data Engineering Technology for Largescale Transaction Processing and Real-Time Complex Analytics) and Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. NRF-2018R1D1A1B07048380).

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Authors and Affiliations

  1. Division of Computer and Information Engineering, Hoseo University, Sechul-ri, Baebang-eup, Asan-si, Chungcheongnam-do, South Korea

    Kwangwon Seo, MyeongSeok Kwak, Yoonmi Shin & Dong-Hyuk Im

  2. Department of Management Information Systems, Jeju National University, Arail-dong, Jeju-si, Jeju-do, South Korea

    Jinhyun Ahn

Authors
  1. Kwangwon Seo
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  2. MyeongSeok Kwak
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  3. Yoonmi Shin
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  4. Jinhyun Ahn
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  5. Dong-Hyuk Im
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Corresponding author

Correspondence to Jinhyun Ahn .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul, Korea (Republic of)

    James J. Park

  2. Department of Computer Software Engineering, Soon Chun Hyang University, Asan, Korea (Republic of)

    Doo-Soon Park

  3. Department of Multimedia Engineering, Dongguk University, Seoul, Korea (Republic of)

    Young-Sik Jeong

  4. Department of Computer Science, Georgia State University, Atlanta, GA, USA

    Yi Pan

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Seo, K., Kwak, M., Shin, Y., Ahn, J., Im, DH. (2020). Parallel Bidirectional Shortest Path Computation in Graphs Using Relational Database Management Systems (RDBMSs). In: Park, J., Park, DS., Jeong, YS., Pan, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2018 2018. Lecture Notes in Electrical Engineering, vol 536. Springer, Singapore. https://doi.org/10.1007/978-981-13-9341-9_12

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  • DOI: https://doi.org/10.1007/978-981-13-9341-9_12

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9340-2

  • Online ISBN: 978-981-13-9341-9

  • eBook Packages: EngineeringEngineering (R0)

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