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

被引:3
作者
Hamilton Adoni, Wilfried Yves [1 ]
Nahhal, Tarik [1 ]
Aghezzaf, Brahim [1 ]
Elbyed, Abdeltif [1 ]
机构
[1] Hassan II Univ, Fac Sci Casablanca, LIMSAD, Km 8 Route EI Jadida,BP 5366, Casablanca 20100, Morocco
来源
UBIQUITOUS NETWORKING, UNET 2017 | 2017年 / 10542卷
关键词
A* algorithm; Large-scale graph; Shortest path problem; Hadoop; MapReduce; Parallel and distributed computing; ALGORITHMS;
D O I
10.1007/978-3-319-68179-5_34
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:390 / 401
页数:12
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