Optimal distance labeling schemes for trees

Ofer Freedman, Paweł Gawrychowski, Patrick K. Nicholson, Oren Weimann

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Labeling schemes seek to assign a short label to each node in a network, so that a function on two nodes (such as distance or adjacency) can be computed by examining their labels alone. For the particular case of trees, following a long line of research, optimal bounds (up to loworder terms)were recently obtained for adjacency labeling [FOCS '15], nearest common ancestor labeling [SODA '14], and ancestry labeling [SICOMP '06]. In this paper we obtain optimal bounds for distance labeling. We present labels of size 1/4 log2 n + o(log2 n), matching (up to low order terms) the recent 1/4 log2 n - O(log n) lower bound [ICALP '16]. Prior to our work, all distance labeling schemes for trees could be reinterpreted as universal trees. A tree T is said to be universal if any tree on n nodes can be found as a subtree of T. A universal tree with /T/ nodes implies a distance labeling scheme with label size log /T/. In 1981, Chung et al. proved that any distance labeling scheme based on universal trees requires labels of size 1/2 log2 n - log n · log log n + O(log n). Our scheme is the first to break this lower bound, showing a separation between distance labeling and universal trees. The Θ(log2 n) barrier for distance labeling in trees has led researchers to consider distances bounded by k. The size of such labels was shown to be log n + O(k √log n) in [WADS '01], and then improved to log n + O(k2 log(k log n)) in [SODA '03] and finally to log n + O(k log(k log(n/k))) in [PODC '07]. We show how to construct labels whose size is the minimum between log n + O(k log((log n)/k)) and O(log n·log(k/ log n)). We complement this with almost tight lower bounds of log n + Ω(k log(log n/(k log k))) and Ω(log n·log(k/ log n)). Finally, we consider (1+ϵ)-approximate distances. We show that the recent labeling scheme of [ICALP '16] can be easily modified to obtain an O(log(1/ϵ) · log n) upper bound and we prove a matching Ω(log(1/ϵ) · log n) lower bound.

Original languageEnglish
Title of host publicationPODC 2017 - Proceedings of the ACM Symposium on Principles of Distributed Computing
PublisherAssociation for Computing Machinery
Number of pages10
ISBN (Electronic)9781450349925
StatePublished - 26 Jul 2017
Event36th ACM Symposium on Principles of Distributed Computing, PODC 2017 - Washington, United States
Duration: 25 Jul 201727 Jul 2017

Publication series

NameProceedings of the Annual ACM Symposium on Principles of Distributed Computing
VolumePart F129314


Conference36th ACM Symposium on Principles of Distributed Computing, PODC 2017
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© 2017 Association for Computing Machinery.


  • Labeling scheme
  • Universal tree

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications


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