Four Shades of Deterministic Leader Election in Anonymous Networks
Barun Gorain, Avery Miller, Andrzej Pelc

TL;DR
This paper compares four variants of leader election in anonymous networks, showing that the weakest form requires exponentially less initial information than the strong forms for minimum-time solutions.
Contribution
It introduces a comparison of four leader election formulations in anonymous networks and quantifies the advice complexity needed for each in minimum time.
Findings
Weak leader election in minimum time needs exponentially less advice than strong versions.
Strong formulations require significantly more initial information to achieve minimum-time election.
The study highlights the complexity gap between weak and strong leader election in anonymous networks.
Abstract
Leader election is one of the fundamental problems in distributed computing: a single node, called the leader, must be specified. This task can be formulated either in a weak way, where one node outputs 'leader' and all other nodes output 'non-leader', or in a strong way, where all nodes must also learn which node is the leader. If the nodes of the network have distinct identifiers, then such an agreement means that all nodes have to output the identifier of the elected leader. For anonymous networks, the strong version of leader election requires that all nodes must be able to find a path to the leader, as this is the only way to identify it. For any network in which leader election (weak or strong) is possible knowing the map of the network, there is a minimum time in which this can be done. We consider four formulations of leader election discussed in the literature in the context of…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsCryptography and Data Security · Privacy-Preserving Technologies in Data · Distributed systems and fault tolerance
