An approximation algorithm for shortest path based on the hierarchy networks

TL;DR

This paper introduces a hierarchical approximation algorithm for shortest path computation in large networks, significantly reducing computational complexity while maintaining high accuracy.

Contribution

It presents a novel hierarchical approach that condenses central nodes into super nodes, enabling efficient and accurate shortest path approximation in large-scale networks.

Findings

Achieves high efficiency in large networks

Maintains high accuracy compared to existing algorithms

Effective in approximating shortest paths with reduced computation

Abstract

It is a critical issue to compute the shortest paths between nodes in networks. Exact algorithms for shortest paths are usually inapplicable for large scale networks due to the high computational complexity. In this paper, we propose a novel algorithm that is applicable for large networks with high efficiency and accuracy. The basic idea of our algorithm is to iteratively construct higher level hierarchy networks by condensing the central nodes and their neighbors into super nodes until the scale of the top level network is very small. Then the algorithm approximates the distances of the shortest paths in the original network with the help of super nodes in the higher level hierarchy networks. The experiment results show that our algorithm achieves both good efficiency and high accuracy compared with other algorithms.