# On computing distances and latencies in Link Streams

## TL;DR

This paper introduces efficient algorithms for computing distances, latencies, and shortest paths in link streams, aiding the analysis of temporal networks and their centrality measures.

## Contribution

It presents novel algorithms with correctness proofs and complexity bounds for analyzing link streams, facilitating the computation of centrality metrics.

## Key findings

- Algorithms for shortest paths and latencies are correct and efficient.
- Complexity bounds are established based on link stream parameters.
- The methods enable better analysis of temporal network centrality.

## Abstract

Link Streams were proposed a few years ago as a model of temporal networks. We seek to understand the topological and temporal nature of those objects through efficiently computing the distances, latencies and lengths of shortest fastest paths. We develop different algorithms to compute those values efficiently. Proofs of correctness for those methods are presented as well as bounds on their temporal complexities as functions of link stream parameters. One purpose of this study is to help develop algorithms to compute centrality functions on link streams such as the betweenness centrality and the closeness centrality.