A Distributed Solution for Efficient K Shortest Paths Computation over Dynamic Road Networks

TL;DR

This paper introduces KSP-DG, a distributed algorithm that efficiently computes multiple shortest paths in dynamic road networks by partitioning the graph and using a novel index, enabling scalable real-time queries.

Contribution

It presents the first distributed solution for k-shortest paths in dynamic road networks, leveraging graph partitioning and a new index for efficiency and scalability.

Findings

Outperforms baseline methods in real road network experiments.

Achieves low maintenance cost in dynamic traffic conditions.

Enables parallel processing of KSP queries on distributed systems.

Abstract

The problem of identifying the k-shortest paths KSPs for short in a dynamic road network is essential to many location-based services. Road networks are dynamic in the sense that the weights of the edges in the corresponding graph constantly change over time, representing evolving traffic conditions. Very often such services have to process numerous KSP queries over large road networks at the same time, thus there is a pressing need to identify distributed solutions for this problem. However, most existing approaches are designed to identify KSPs on a static graph in a sequential manner, restricting their scalability and applicability in a distributed setting. We therefore propose KSP-DG, a distributed algorithm for identifying k-shortest paths in a dynamic graph. It is based on partitioning the entire graph into smaller subgraphs, and reduces the problem of determining KSPs into the computation of partial KSPs in relevant subgraphs, which can execute in parallel on a cluster of servers. A distributed two-level index called DTLP is developed to facilitate the efficient identification of relevant subgraphs. A salient feature of DTLP is that it indexes a set of virtual paths that are insensitive to varying traffic conditions in an efficient and compact fashion, leading to very low maintenance cost in dynamic road networks. This is the first treatment of the problem of processing KSP queries over dynamic road networks. Extensive experiments conducted on real road networks confirm the superiority of our proposal over baseline methods.