• DocumentCode
    25786
  • Title

    Information Equals Amortized Communication

  • Author

    Braverman, Mark ; Rao, Akhila

  • Author_Institution
    Dept. of Comput. Sci., Princeton Univ., Princeton, NJ, USA
  • Volume
    60
  • Issue
    10
  • fYear
    2014
  • fDate
    Oct. 2014
  • Firstpage
    6058
  • Lastpage
    6069
  • Abstract
    We show how to efficiently simulate the sending of a single message M to a receiver who has partial information about the message, so that the expected number of bits communicated in the simulation is close to the amount of additional information that the message reveals to the receiver. This is a generalization and strengthening of the Slepian-Wolf theorem, which shows how to carry out such a simulation with low amortized communication in the case that M is a deterministic function of X. A caveat is that our simulation is interactive. As a consequence, we prove that the internal information cost (namely the information revealed to the parties) involved in computing any relation or function using a two party interactive protocol is exactly equal to the amortized communication complexity of computing independent copies of the same relation or function. We also show that the only way to prove a strong direct sum theorem for randomized communication complexity is by solving a particular variant of the pointer jumping problem that we define. This paper implies that a strong direct sum theorem for communication complexity holds if and only if efficient compression of communication protocols is possible. In particular, together with our result, a recent result of Ganor, Kol, and Raz implies that the strongest version of direct sum for randomized communication complexity is false.
  • Keywords
    information theory; protocols; Slepian-Wolf theorem; amortized communication complexity; direct sum theorem; internal information cost; partial information; party interactive protocol; pointer jumping problem; randomized communication complexity direct sum; Complexity theory; Entropy; Mutual information; Protocols; Random variables; Receivers; Communication complexity; compression; interactive communication;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2014.2347282
  • Filename
    6877708