Towards Constant Time Multi-Call Rumor Spreading on Small-Set Expanders

August 25, 2025 Β· Declared Dead Β· πŸ› International Symposium on Distributed Computing

πŸ‘» CAUSE OF DEATH: Ghosted
No code link whatsoever

"No code URL or promise found in abstract"

Evidence collected by the PWNC Scanner

Authors Emilio Cruciani, Sebastian Forster, Tijn de Vos arXiv ID 2508.18017 Category cs.DS: Data Structures & Algorithms Citations 0 Venue International Symposium on Distributed Computing Last Checked 4 months ago
Abstract
We study a multi-call variant of the classic PUSH&PULL rumor spreading process where nodes can contact $k$ of their neighbors instead of a single one during both PUSH and PULL operations. We show that rumor spreading can be made faster at the cost of an increased amount of communication between the nodes. As a motivating example, consider the process on a complete graph of $n$ nodes: while the standard PUSH&PULL protocol takes $Θ(\log n)$ rounds, we prove that our $k$-PUSH&PULL variant completes in $Θ(\log_{k} n)$ rounds, with high probability. We generalize this result in an expansion-sensitive way, as has been done for the classic PUSH&PULL protocol for different notions of expansion, e.g., conductance and vertex expansion. We consider small-set vertex expanders, graphs in which every sufficiently small subset of nodes has a large neighborhood, ensuring strong local connectivity. In particular, when the expansion parameter satisfies $Ο†> 1$, these graphs have a diameter of $o(\log n)$, as opposed to other standard notions of expansion. Since the graph's diameter is a lower bound on the number of rounds required for rumor spreading, this makes small-set expanders particularly well-suited for fast information dissemination. We prove that $k$-PUSH&PULL takes $O(\log_Ο† n \cdot \log_{k} n)$ rounds in these expanders, with high probability. We complement this with a simple lower bound of $Ξ©(\log_Ο† n+ \log_{k} n)$ rounds.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

πŸ“œ Similar Papers

In the same crypt β€” Data Structures & Algorithms

Died the same way β€” πŸ‘» Ghosted