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Effects of Topology Knowledge and Relay Depth on Asynchronous Appoximate Consensus

Authors Dimitris Sakavalas, Lewis Tseng, Nitin H. Vaidya

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Author Details

Dimitris Sakavalas
  • Boston College, USA
Lewis Tseng
  • Boston College, USA
Nitin H. Vaidya
  • Georgetown University, USA

Funding

  • Vaidya, Nitin H.: This research is supported in part by National Science Foundation awards 1421918. Any opinions, findings, and conclusions or recommendations expressed here are those of the authors and do not necessarily reflect the views of the funding agencies or the U.S. government.

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Dimitris Sakavalas, Lewis Tseng, and Nitin H. Vaidya. Effects of Topology Knowledge and Relay Depth on Asynchronous Appoximate Consensus. In 22nd International Conference on Principles of Distributed Systems (OPODIS 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 125, pp. 14:1-14:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/LIPIcs.OPODIS.2018.14

Abstract

Consider a point-to-point message-passing network. We are interested in the asynchronous crash-tolerant consensus problem in incomplete networks. We study the feasibility and efficiency of approximate consensus under different restrictions on topology knowledge and the relay depth, i.e., the maximum number of hops any message can be relayed. These two constraints are common in large-scale networks, and are used to avoid memory overload and network congestion respectively. Specifically, for positive integer values k and k', we consider that each node knows all its neighbors of at most k-hop distance (k-hop topology knowledge), and the relay depth is k'. We consider both directed and undirected graphs. More concretely, we answer the following question in asynchronous systems: "What is a tight condition on the underlying communication graphs for achieving approximate consensus if each node has only a k-hop topology knowledge and relay depth k'?" To prove that the necessary conditions presented in the paper are also sufficient, we have developed algorithms that achieve consensus in graphs satisfying those conditions: - The first class of algorithms requires k-hop topology knowledge and relay depth k. Unlike prior algorithms, these algorithms do not flood the network, and each node does not need the full topology knowledge. We show how the convergence time and the message complexity of those algorithms is affected by k, providing the respective upper bounds. - The second set of algorithms requires only one-hop neighborhood knowledge, i.e., immediate incoming and outgoing neighbors, but needs to flood the network (i.e., relay depth is n, where n is the number of nodes). One result that may be of independent interest is a topology discovery mechanism to learn and "estimate" the topology in asynchronous directed networks with crash faults.

Subject Classification

ACM Subject Classification
  • Computer systems organization → Fault-tolerant network topologies
Keywords
  • Asynchrony
  • crash
  • consensus
  • incomplete graphs
  • topology knowledge

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