The MapReduce based approach to improve the all-pair shortest path computation

Lau Nguyen Dinh
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Abstract

When building sequential algorithms for problems on the graphic network, the algorithms themselves are not only very complex but the complexity of the algorithms also is very big. Thus, sequential algorithms must be parralled to share work and reduce computation time. For above reasons, it is crucial to build parallelization of algorithms in extended graph to find the shortest path. Therefore, a study of algorithm finding the shortest path from a source node to all nodes in the MapReduce architectures is essential to deal with many real problems with huge input data in our daily life. MapReduce architectures processes on (Key, Value) pairs are independent between processes, so multiple processes can be assigned to execute simultaneously on the Hodoop system to reduce calculation time
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基于 MapReduce 的全对最短路径计算改进方法
在构建图形网络问题的顺序算法时,不仅算法本身非常复杂,而且算法的复杂度也非常大。因此,必须对顺序算法进行解析,以分担工作并减少计算时间。基于上述原因,在扩展图中建立算法的并行化对于寻找最短路径至关重要。因此,研究在 MapReduce 架构中寻找从源节点到所有节点的最短路径的算法,对于处理日常生活中许多输入数据量巨大的实际问题至关重要。MapReduce 架构中关于(Key,Value)对的进程之间是独立的,因此可以分配多个进程在 Hodoop 系统上同时执行,以减少计算时间。
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