An efficient index method for the optimal path query over multi-cost networks

In the past couple of decades, graphs have been widely used to model complex relationships among various entities in real applications. Shortest path query is a fundamental problem in graphs and has been well-studied. Most existing approaches for the shortest path problem consider that there is only one kind of cost in networks. However, there always are several kinds of cost in networks and users prefer to select an optimal path under the global consideration of these kinds of cost. In this paper, we study the problem of finding the optimal path in the multi-cost networks. We prove this problem is NP-hard and the existing index techniques cannot be used to this problem. We propose a novel partition-based index with contour skyline techniques to find the optimal path. We propose a vertex-filtering algorithm to facilitate the query processing. We conduct extensive experiments on six real-life networks and the experimental results show that our method has an improvement in efficiency by an order of magnitude compared to the previous heuristic algorithms.