Linear Path Skyline Computation in Bicriteria Networks

A bicriteria network is an interlinked data set where edges are labeled with two cost attributes. An example is a road network where edges represent road segments being labeled with traversal time and energy consumption. To measure the proximity of two nodes in network data, the common method is to compute a cost optimal path between the nodes. In a bicriteria network, there often is no unique path being optimal w.r.t. both types of cost. Instead, a path skyline describes the set of non-dominated paths that are optimal under varying preference functions. In this paper, we examine the subset of the path skyline which is optimal under the most common type of preference function, the weighted sum. We will examine characteristics of this more strict domination relation. Furthermore, we introduce techniques to efficiently maintain the set of linearly non-dominated paths. Finally, we will introduce a new algorithm to compute all linearly non-dominated paths denoted as linear path skyline. In our experimental evaluation, we will compare our new approach to other methods for computing the linear skyline and efficient approaches to compute path skylines.