Collective asynchronous reading with polylogarithmic worst-case overhead

  • Authors:
  • Bogdan S. Chlebus;Dariusz R. Kowalski;Alexander A. Shvartsman

  • Affiliations:
  • University of Colorado at Denver, Denver, CO;Max-Planck-Institut fur Informatik, Saarbrucken, Germany and Uniwersytet Warszawski, Warszawa, Poland;University of Connecticut, Storrs, CT and CSAIL, Massachusetts Institute of Technology, Cambridge, MA

  • Venue:
  • STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
  • Year:
  • 2004

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Abstract

The Collect problem for an asynchronous shared-memory system has the objective for the processors to learn all values of a collection of shared registers, while minimizing the total number of read and write operations. First abstracted by Saks, Shavit, and Woll [37], Collect is among the standard problems in distributed computing, The model consists of $n$ asynchronous processes, each with a single-writer multi-reader register of a polynomial capacity. The best previously known deterministic solution performs O(n3/2log n) reads and writes, and it is due to Ajtai, Aspnes, Dwork, and Waarts [3]. This paper presents a new deterministic algorithm that performs O(n log7 n) read/write operations, thus substantially improving the best previous upper bound. Using an approach based on epidemic rumor-spreading, the novelty of the new algorithm is in using a family of expander graphs and ensuring that each of the successive groups of processes collect and propagate sufficiently many rumors to the next group. The algorithm is adapted to the Repeatable Collect problem, which is an on-line version. The competitive latency of the new algorithm is O(log7 n) vs. the much higher competitive latency O(√nlog n) given in [3]. A result of independent interest in this paper abstracts a gossiping game that is played on a graph and that gives its payoff in terms of expansion.