Andrea Collevecchio

dblp:150/1195 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2017
0000-0001-9444-3600ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1Theory of computation · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Distributed computing theory · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Distributed computing theory › information dissemination
gossip and rumor spreading
0.212015
On the Push&Pull Protocol for Rumour Spreading: [Extended Abstract] · PODC 2015
Distributed computing theory › information dissemination
push-pull protocol
0.212015
On the Push&Pull Protocol for Rumour Spreading: [Extended Abstract] · PODC 2015
Distributed computing theory › distributed algorithms
randomized distributed algorithms
0.112015
On the Push&Pull Protocol for Rumour Spreading: [Extended Abstract] · PODC 2015

Methods — techniques the papers use, named apart from their topics

random graph analysis · 0.2exponential clocks · 0.2
YearPublicationVenuePosition
2017 On the Push&Pull Protocol for Rumor Spreading
abstract
The asynchronous push&pull protocol, a randomized distributed algorithm for spreading a rumor in a graph $G$, is defined as follows. Independent exponential clocks of rate 1 are associated with the vertices of $G$, one to each vertex. Initially, one vertex of $G$ knows the rumor. Whenever the clock of a vertex $x$ rings, it calls a random neighbor $y$: if $x$ knows the rumor and $y$ does not, then $x$ tells $y$ the rumor (a push operation), and if $x$ does not know the rumor and $y$ knows it, $y$ tells $x$ the rumor (a pull operation). The average spread time of $G$ is the expected time it takes for all vertices to know the rumor, and the guaranteed spread time of $G$ is the smallest time $t$ such that with probability at least $1 - 1/n$, after time $t$ all vertices know the rumor. The synchronous variant of this protocol, in which each clock rings precisely at times $1,2,\dots$, has been studied extensively. We prove the following results for any $n$-vertex graph: In either version, the average spread time is at most linear even if only the pull operation is used, and the guaranteed spread time is within a logarithmic factor of the average spread time, so it is $O(n \log n)$. In the asynchronous version, both the average and guaranteed spread times are $\Omega(\log n)$. We give examples of graphs illustrating that these bounds are best possible up to constant factors. We also prove the first analytical relationships between the guaranteed spread times in the two versions. First, in all graphs the guaranteed spread time in the asynchronous version is within an $O(\log n)$ factor of that in the synchronous version, and this is tight. Next, we find examples of graphs whose asynchronous spread times are logarithmic, but the synchronous versions are polynomially large. Finally, we show for any graph that the ratio of the guaranteed synchronous spread time to the guaranteed asynchronous spread time is $O\big(n^{2/3}\big)$.
Hüseyin Acan, Andrea Collevecchio, Abbas Mehrabian, Nicholas C. Wormald
SIAM J. Discret. Math.2
2015 On the Push&Pull Protocol for Rumour Spreading: [Extended Abstract]
abstract
The asynchronous push&pull protocol, a randomized distributed algorithm for spreading a rumour in a graph G, is defined as follows. Independent exponential clocks of rate 1 are associated with the vertices of G, one to each vertex. Initially, one vertex of G knows the rumour. Whenever the clock of a vertex x rings, it calls a random neighbour y: if x knows the rumour and y does not, then x tells y the rumour (a push operation), and if x does not know the rumour and y knows it, y tells x the rumour (a pull operation). The average spread time of G is the expected time it takes for all vertices to know the rumour, and the guaranteed spread time of G is the smallest time t such that with probability at least 1 - 1/n, after time t all vertices know the rumour. The synchronous variant of this protocol, in which each clock rings precisely at times 1,2,..., has been studied extensively.
Hüseyin Acan, Andrea Collevecchio, Abbas Mehrabian, Nicholas C. Wormald
PODC2