Fast Graphical Population Protocols
Fast Graphical Population Protocols
复制标题
快速图形人口协议
DOI:
10.4230/lipics.opodis.2021.14
复制
发表时间:
2021
期刊:
影响因子:
--
通讯作者:
Joel Rybicki
中科院分区:
文献类型:
--
作者:
Dan Alistarh;Rati Gelashvili;Joel Rybicki
Let $G$ be a graph on $n$ nodes. In the stochastic population protocol model, a collection of $n$ indistinguishable, resource-limited nodes collectively solve tasks via pairwise interactions. In each interaction, two randomly chosen neighbors first read each other's states, and then update their local states. A rich line of research has established tight upper and lower bounds on the complexity of fundamental tasks, such as majority and leader election, in this model, when $G$ is a clique. Specifically, in the clique, these tasks can be solved fast, i.e., in $n \operatorname{polylog} n$ pairwise interactions, with high probability, using at most $\operatorname{polylog} n$ states per node. In this work, we consider the more general setting where $G$ is an arbitrary graph, and present a technique for simulating protocols designed for fully-connected networks in any connected regular graph. Our main result is a simulation that is efficient on many interesting graph families: roughly, the simulation overhead is polylogarithmic in the number of nodes, and quadratic in the conductance of the graph. As a sample application, we show that, in any regular graph with conductance $\phi$, both leader election and exact majority can be solved in $\phi^{-2} \cdot n \operatorname{polylog} n$ pairwise interactions, with high probability, using at most $\phi^{-2} \cdot \operatorname{polylog} n$ states per node. This shows that there are fast and space-efficient population protocols for leader election and exact majority on graphs with good expansion properties. We believe our results will prove generally useful, as they allow efficient technology transfer between the well-mixed (clique) case, and the under-explored spatial setting.
DOI:
10.1137/120900368
发表时间:
2012-04
期刊:
SIAM J. Discret. Math.
影响因子:
--
作者:
C. Cooper;Robert Elsässer;H. Ono;T. Radzik
通讯作者:
C. Cooper;Robert Elsässer;H. Ono;T. Radzik
DOI:
10.1109/focs52979.2021.00104
发表时间:
2022-02
期刊:
2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS)
影响因子:
--
作者:
David Doty;Mahsa Eftekhari;L. Gąsieniec;Eric E. Severson;P. Uznański;Grzegorz Stachowiak
通讯作者:
David Doty;Mahsa Eftekhari;L. Gąsieniec;Eric E. Severson;P. Uznański;Grzegorz Stachowiak
DOI:
10.1137/1.9781611974782.169
发表时间:
2016-02
期刊:
ArXiv
影响因子:
--
作者:
Dan Alistarh;J. Aspnes;David Eisenstat;Rati Gelashvili;R. Rivest
通讯作者:
Dan Alistarh;J. Aspnes;David Eisenstat;Rati Gelashvili;R. Rivest