Best Upgrade Plans for Large Road Networks

Abstract

Abstract. In this paper, we consider a new problem in the context of road network databases, named Resource Constrained Best Upgrade Plan computation (BUP, for short). Consider a transportation network (weighted graph) G where a subset of the edges are upgradable, i.e., for each such edge there is a cost, which if spent, the weight of the edge can be reduced to a specific new value. Given a source and a destination in G, and a budget (resource constraint) B, the BUP problem is to identify which upgradable edges should be upgraded so that the shortest path distance between source and destination (in the updated network) is minimized, without exceeding the available budget for the upgrade. In addition to transportation networks, the BUP query arises in other domains too, such as telecommunications. We propose a framework for BUP processing and evaluate it with experiments on large, real road networks.

Spatio-temporal propagation of cascading overload failures in spatially embedded networks

“…To explore the possibility of universal feature in overload propagation, here we analyse the propagation of cascading overload failures on different network models and realistic networks. Besides the model networks including lattice, circular lattice, planar graph and circular plate, we also study the overload propagation on the realistic road networks 29 . We initiate a local attack in the geographical centre of these spatially embedded networks and analyse the spatio-temporal evolution of r c and F r .…”