Abstract
In this paper, we present a contribution for the Single Source Shortest Path Problem (SSSPP) in large-scale graph with A* algorithm. A* is one of the most efficient graph traversal algorithm because it is driven by a heuristic which determines the optimal path. A* approach is not efficient when the graph is too large to be processed due to exponential time complexity. We propose a MapReduce-based approach called MRA*: MapReduce-A* which consists to combine the A* algorithm with MapReduce paradigm to compute the shortest path in parallel and distributed environment. We perform experiments in a Hadoop multi-node cluster and our results prove that the proposed approach outperforms A* algorithm and reduces significantly the computational time.
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Acknowledgments
We would like to thank Pr Tarik Nahhal, Pr Brahim Aghezzaf and Pr Abdeltif Elbyed for their useful remarks about this work.
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Adoni, W.Y.H., Nahhal, T., Aghezzaf, B., Elbyed, A. (2017). MRA*: Parallel and Distributed Path in Large-Scale Graph Using MapReduce-A* Based Approach. In: Sabir, E., García Armada, A., Ghogho, M., Debbah, M. (eds) Ubiquitous Networking. UNet 2017. Lecture Notes in Computer Science(), vol 10542. Springer, Cham. https://doi.org/10.1007/978-3-319-68179-5_34
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DOI: https://doi.org/10.1007/978-3-319-68179-5_34
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