Shortest Path Algorithm Based on Community Detection

Abstract

To overcome the performance limitation of traditional shortest path algorithms when processing large amount of calculation in large scale networks, this article proposes a novel shortest path algorithm based on community detection. In the proposed algorithm, community detection is utilized to integrate the necessary but tedious information in the network and reduce the scale of the network, which accelerates the calculation. Particularly, when processing multiple shortest path queries, the community information can be reused, which leads to considerable improvement of the efficiency. Based on the results in performance evaluation, it turns out that in middle (500 nodes) and large-scale (1500 or 5000 nodes) BA networks, our algorithm is more efficient than traditional Dijkstra’s algorithm in both single query (5%- 138%) and multiple query (104%-3905%).