Robust Distance Queries on Massive Networks

  • Daniel Delling
  • Andrew V. Goldberg
  • Thomas Pajor
  • Renato F. Werneck
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8737)


We present a versatile and scalable algorithm for computing exact distances on real-world networks with tens of millions of arcs in real time. Unlike existing approaches, preprocessing and queries are practical on a wide variety of inputs, such as social, communication, sensor, and road networks. We achieve this by providing a unified approach based on the concept of 2-hop labels, improving upon existing methods. In particular, we introduce a fast sampling-based algorithm to order vertices by importance, as well as effective compression techniques.


Short Path Road Network Betweenness Centrality Query Time Graph Class 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Daniel Delling
    • 1
  • Andrew V. Goldberg
    • 1
  • Thomas Pajor
    • 1
  • Renato F. Werneck
    • 1
  1. 1.Microsoft ResearchUSA

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