A distributed computation of the shortest path in large-scale road network

The shortest path solution in large-scale road network has become a hot topic. How to find a shortest path efficiently and quickly in a road network is very difficult. With the development of parallel computing and the improvement of Hadoop ecology, it makes it easier to solve the problem by using the MapReduce model in the Hadoop ecosystem. In this paper, we propose a improved shortest path algorithm based on cloud computing in large data architecture. The principle of this algorithm is to divide the whole large-scale road network into small-scale road network according to a certain distance, calculate the shortest path of small-scale road network, and finally combine these shortest paths into the shortest path of large-scale road network. The experimental results show that the algorithm has good results, especially with the increase of computing nodes, and the efficiency of calculation is higher.