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MRA*: Parallel and Distributed Path in Large-Scale Graph Using MapReduce-A* Based Approach

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Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 10542))

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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Correspondence to Tarik Nahhal .

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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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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68178-8

  • Online ISBN: 978-3-319-68179-5

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