Rumour spreading and graph conductance
Flavio Chierichetti,Silvio Lattanzi,Alessandro Panconesi +2 more
- pp 1657-1663
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TLDR
It is shown that if a connected graph with n nodes has conductance φ then rumour spreading, also known as randomized broadcast, successfully broadcasts a message within O(log4n/φ6) many steps, with high probability, using the PUSH-PULL strategy.Abstract:
We show that if a connected graph with n nodes has conductance φ then rumour spreading, also known as randomized broadcast, successfully broadcasts a message within O(log4n/φ6) many steps, with high probability, using the PUSH-PULL strategy. An interesting feature of our approach is that it draws a connection between rumour spreading and the spectral sparsification procedure of Spielman and Teng [23].read more
Citations
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Journal ArticleDOI
Mobile Data Offloading through Opportunistic Communications and Social Participation
TL;DR: This work proposes to exploit opportunistic communications to facilitate information dissemination in the emerging Mobile Social Networks (MoSoNets) and thus reduce the amount of mobile data traffic.
Proceedings ArticleDOI
Cellular traffic offloading through opportunistic communications: a case study
TL;DR: This work investigates the target-set selection problem for information delivery in the emerging Mobile Social Networks (MoSoNets), and proposes three algorithms, called Greedy, Heuristic, and Random, to exploit opportunistic communications to facilitate the information dissemination and thus reduce the amount of cellular traffic.
Journal ArticleDOI
Spectral sparsification of graphs: theory and algorithms
TL;DR: It is explained what it means for one graph to be a spectral approximation of another and the development of algorithms for spectral sparsification are reviewed, including a faster algorithm for finding approximate maximum flows and minimum cuts in an undirected network.
Proceedings ArticleDOI
Tight bounds for rumor spreading in graphs of a given conductance
TL;DR: It is shown that for any n-node graph with conductance, the classical PUSH-PULL algorithm distributes a rumor to all nodes of the graph in O( 1 logn) rounds with high probability (w.h.p.); this bound improves a recent result of Chierichetti, Lattanzi, and Panconesi [6].
References
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Book
Spectral Graph Theory
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Proceedings ArticleDOI
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Proceedings ArticleDOI
Gossip-based computation of aggregate information
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Concentration of Measure for the Analysis of Randomized Algorithms
TL;DR: In this paper, the authors present a coherent and unified treatment of probabilistic techniques for obtaining high probability estimates on the performance of randomized algorithms, from the basic tool kit from the Chernoff-Hoeffding (CH) bounds to more sophisticated techniques like Martingales and isoperimetric inequalities, as well as some recent developments like Talagrand's inequality, transportation cost inequalities, and log-Sobolev inequalities.