The Research of Dynamic Shortest Path Based on Cloud Computing

Recently, it has been shown that solving the shortest path problem in large-scale real-road networks based on MapReduce play an important role in dynamic traffic management, traffic signal control and mitigation of urban traffic congestion. We focus on the design of an efficient MapReduce-based approach since a classical shortest path algorithm is not suitable to accomplish efficiently such task. Our objective is not to guarantee the optimality but to provide high quality solutions in acceptable computational time. The proposed approach consists in partitioning the original graph into a set of subgraphs, then solving the shortest path on each subgraph in a parallel way to obtain a solution for the original graph. An iterative improvement procedure is introduced to improve the solution. The results of the experiment show that such approach achieves significant gain of computational time.