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Brief Announcement: Efficient Computation in Congested Anonymous Dynamic Networks

Published: 16 June 2023 Publication History

Abstract

An anonymous dynamic network is a network of indistinguishable processes whose communication links may appear or disappear unpredictably over time. Previous research has shown that deter-ministically computing an arbitrary function of a multiset of input values given to these processes takes only a linear number of communication rounds (Di Luna-Viglietta, FOCS 2022).
However, fast algorithms for anonymous dynamic networks rely on the construction and transmission of large data structures called history trees, whose size is polynomial in the number of processes. This approach is unfeasible if the network is congested, and only messages of logarithmic size can be sent through its links. In fact, it is known that certain basic tasks such as all-to-all token dissemination (by means of single-token forwarding) require Ω(n2/log n) rounds in congested networks (Dutta et al., SODA 2013).
In this work, we develop a series of practical and efficient techniques that make it possible to use history trees in congested anonymous dynamic networks. Among other applications, we show how to compute arbitrary functions in such networks in O(n3) communication rounds, greatly improving upon previous state-of-the-art algorithms for congested networks.

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cover image ACM Conferences
PODC '23: Proceedings of the 2023 ACM Symposium on Principles of Distributed Computing
June 2023
392 pages
ISBN:9798400701214
DOI:10.1145/3583668
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Published: 16 June 2023

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Author Tags

  1. anonymous dynamic network
  2. congested network
  3. history tree

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PODC '23 Paper Acceptance Rate 29 of 110 submissions, 26%;
Overall Acceptance Rate 740 of 2,477 submissions, 30%

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