A Multithreaded-BFS Algorithm for Optimizing the Graph Computation in Multicore Processing System
Graphs are the most complex data structure that involves heavy mathematical computations. Various real-time applications use the graph at storage, processing, object characterization, and behavior specification stages. The connectivity analysis, coverage building, and routing are the critical applic...
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| Published in: | Procedia computer science Vol. 233; pp. 138 - 146 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier B.V
2024
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| Subjects: | |
| ISSN: | 1877-0509, 1877-0509 |
| Online Access: | Get full text |
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| Summary: | Graphs are the most complex data structure that involves heavy mathematical computations. Various real-time applications use the graph at storage, processing, object characterization, and behavior specification stages. The connectivity analysis, coverage building, and routing are the critical applications of graph evaluation. Various associated applications need the exploration of a graph with a practical and real-time outcome. The processing of larger graphs is a big challenge for the researcher. In this paper, a hybrid graph-based computation optimization method is designed to optimize the performance of graph processing in multi-core processors. The BFS algorithm is applied over the multiple processors to optimize the functional response. The multithreaded-BFS is implemented to reduce the time of graph processing and computation. The proposed algorithm is implemented in the OpenMP environment. The experimentation is done on two-core and four-core processors. The experiment is conducted on a 100 to 1000-node network. The traversing and graph coloring algorithms are implemented for the analysis. The comparative analysis is conducted on single-core and multi-core processors with DFS and BFS-based algorithms. The analysis results identified that the proposed algorithm reduced the processing time effectively. |
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| ISSN: | 1877-0509 1877-0509 |
| DOI: | 10.1016/j.procs.2024.03.203 |