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On different modes of communication

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Published:01 January 1988Publication History

ABSTRACT

We compare the communication complexity of discrete functions under different modes of computation, unifying and extending several known models. Protocols can be deterministic, nondeterministic or probabilistic and in the last case the error probability may vary. On the other hand communication can be 1-way, 2-way or as an intermediate stage consist of a fixed number k > 1 of rounds.

The following main results are obtained. A square gap between deterministic and nondeterministic communication complexity is shown for a specific function, which is the maximal possible. This improves the results of [MS 82] and [AUY 83]. For probabilistic 1- and 2-way protocols we prove linear lower bounds for functions that satisfy certain independence conditions, extending the results of [Y 79] and [Y 83]. Further, with more technical effort an exponential gap between deterministic k-round and probabilistic (k - 1)-round communication with fixed error probability is obtained. This generalizes the main result of [DGS 84]. On contrast for arbitrary error probabilities less than 1/2 there is no difference between the complexity of 1- and 2-way protocols, extending results of [PS 84]. Finally we consider communication with fixed message length and uniform probability distributions and give simulations of arbitrary protocols by such uniform ones with little overhead.

References

  1. AUY 83.A.V. Aho, J. D. Ullman, M. Yannakakis, "On notions of information transfer in VLSI circuits", Proc. 15th ACM $TOC, 133-139, 1.983 Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. DGS 84.P. Duris, Z. Galil, G. Schnitger, "Lower bounds on communication complexity", Proc. 16th ACM $TOC, 81-89, 1984 Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. HR 87.B. Halstenberg, R. Reischuk, "On different modes of communication", Technical Report TI-1/87, Institut f/Jr Theoretische Informa~ik, Ttt Darmstadt, 1987Google ScholarGoogle Scholar
  4. KS 87.B. Kalyanasundaram, G. Schnitger, "The probabilistic communication complexity of set intersection", Proc. 2rid 1EEE Structure in Complexity Theory, 41-49, 1987Google ScholarGoogle Scholar
  5. MS 82.K. Mehlhorn, E. M. Schmidt, "Las Vegas is better than determinism in VLSI and distributed computing", Proc. 14th ACM STOC, 330-337, 1982 Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. PS 84.R. Paturi, J. Simon, "Probabilistic communication complexity", Proc. 25th iEEE FOCS, 118- 126, 1984 see also J. CSS 33, 1986, 106-124 Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. T 84.P. Tiwari, "Lower bounds on communication complexity in distributed computer networks", Proc. 25th IEEE FOCS, 109-117, 1984 see also J. ACM 34, 1987, 921-938 Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Y 79.A.C. Yao, "Some complexity questions related to distributed computing", Proc. 11th ACM STOC, 209-213, 1979 Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Y 83.A.C. Yao, "Lower bounds by probabilistic arguments", Proc. 24th iEEE FOCS, 420-428, 1983Google ScholarGoogle ScholarDigital LibraryDigital Library

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            cover image ACM Conferences
            STOC '88: Proceedings of the twentieth annual ACM symposium on Theory of computing
            January 1988
            553 pages
            ISBN:0897912640
            DOI:10.1145/62212

            Copyright © 1988 ACM

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            Publication History

            • Published: 1 January 1988

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            STOC '88 Paper Acceptance Rate53of192submissions,28%Overall Acceptance Rate1,469of4,586submissions,32%

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