On large automata processing: towards a high level distributed graph language
by Alpha Mouhamadou Diop; Cheikh Ba
International Journal of Big Data Intelligence (IJBDI), Vol. 8, No. 2, 2024

Abstract: Large graphs or automata have their data that cannot fit in a single machine, or may take unreasonable time to be processed. We implement with MapReduce and Giraph two algorithms for intersecting and minimising large and distributed automata. We provide some comparative analysis, and the experiment results are depicted in figures. Our work experimentally validates our propositions as long as it shows that our choice, in comparison with MapReduce one, is not only more suitable for graph-oriented algorithms, but also speeds the executions up. This work is one of the first steps of a long-term goal that consists in a high level distributed graph processing language.

Online publication date: Tue, 04-Jun-2024

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