A Parallel Framework for Streaming Graphs Computing
Paper
Paper/Presentation Title | A Parallel Framework for Streaming Graphs Computing |
---|---|
Presentation Type | Paper |
Authors | Jiang, Ting, Yu, Ting, Hong, Zexian, Ren, Zujie and Zhang, Ji |
Journal or Proceedings Title | Proceedings of the 10th IEEE International Conference on Big Data (2022) |
Journal Citation | pp. 6673-6675 |
Number of Pages | 3 |
Year | 2023 |
Publisher | IEEE (Institute of Electrical and Electronics Engineers) |
Place of Publication | United States |
Digital Object Identifier (DOI) | https://doi.org/10.1109/BigData55660.2022.10020995 |
Web Address (URL) of Paper | https://ieeexplore.ieee.org/document/10020995 |
Web Address (URL) of Conference Proceedings | https://ieeexplore.ieee.org/xpl/conhome/10020192/proceeding |
Conference/Event | Proceedings of the 10th IEEE International Conference on Big Data (2022) |
Event Details | Proceedings of the 10th IEEE International Conference on Big Data (2022) Parent IEEE International Conference on Big Data Delivery In person Event Date 17 to end of 20 Dec 2022 Event Location Osaka, Japan |
Abstract | Streaming computation for large graphs on parallel systems faces challenges in task decomposition, data skew, and resource scheduling. In this work, we propose a general parallel streaming framework for the node-centered graph algorithms to improve the computation efficiency. We construct the parallel procedure of the incremental maximal clique enumeration (IMCE) task and accelerate the incremental Candidate Map Constructor (CMC) algorithm through the framework for large-scale streaming graphs. Experimental results on three large real-world graphs show the framework’s positive effect on the algorithm’s execution time. |
Keywords | Parallel streaming framework; node-centered graph algorithms; incremental maximal clique enumeration |
ANZSRC Field of Research 2020 | 460599. Data management and data science not elsewhere classified |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Zhejiang Lab, China |
Nanyang Technological University, Singapore | |
University of Southern Queensland |
https://research.usq.edu.au/item/z58z0/a-parallel-framework-for-streaming-graphs-computing
31
total views2
total downloads2
views this month1
downloads this month