Communication complexity and graph families

Sudeshna Kolay, Fahad Panolan, Saket Saurabh

Research output: Contribution to journalArticlepeer-review


Given a graph G and a pair (F1, F2) of graph families, the function GDISJG, F1, F2 takes as input, two induced subgraphsG1 andG2 ofG, such thatG1 ∈ F1 andG2 ∈ F2 and returns 1 ifV(G1) ∩ V(G2) = ∅ and 0 otherwise. We study the communication complexity of this problem in the two-party model. In particular, we look at pairs of hereditary graph families. We show that the communication complexity of this function, when the two graph families are hereditary, is sublinear if and only if there are finitely many graphs in the intersection of these two families. Then, using concepts from parameterized complexity, we obtain nuanced upper bounds on the communication complexity of GDISJG, F1, F2. A concept related to communication protocols is that of a (F1, F2)-separating family of a graph G. A collection F of subsets of V(G) is called a (F1, F2)-separating family for G, if for any two vertex disjoint induced subgraphs G1 ∈ F1,G2 ∈ F2, there is a set F ∈ F with V(G1) ⊆ F andV(G2) ∩ F = ∅. Given a graphG onn vertices, for any pair (F1, F2) of hereditary graph families with sublinear communication complexity for GDISJG, F1, F2, we give an enumeration algorithm that finds a subexponential sized (F1, F2)-separating family. In fact, we give an enumeration algorithm that finds a 2o(k)nO(1) sized (F1, F2)-separating family, where k denotes the size of a minimum sized set S of vertices such that V(G) \ S has a bipartition (V1,V2) with G[V1] ∈ F1 and G[V2] ∈ F2. We exhibit a wide range of applications for these separating families, to obtain combinatorial bounds, enumeration algorithms, as well as exact and FPT algorithms for several problems.

Original languageEnglish
Article number11
JournalACM Transactions on Computation Theory
Issue number2
StatePublished - 1 Apr 2019
Externally publishedYes


  • Communication complexity
  • FPT algorithms
  • Separating family

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computational Theory and Mathematics


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