TY - GEN
T1 - Accelerated Information Dissemination on Networks with Local and Global Edges
AU - Cohen, Sarel
AU - Fischbeck, Philipp
AU - Friedrich, Tobias
AU - Krejca, Martin S.
AU - Sauerwald, Thomas
N1 - Publisher Copyright:
© 2022, Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - Bootstrap percolation is a classical model for the spread of information in a network. In the round-based version, nodes of an undirected graph become active once at least r neighbors were active in the previous round. We propose the perturbed percolation process: a superposition of two percolation processes on the same node set. One process acts on a local graph with activation threshold 1, the other acts on a global graph with threshold r – representing local and global edges, respectively. We consider grid-like local graphs and expanders as global graphs on n nodes. For the extreme case r= 1, all nodes are active after O(log n) rounds, while the process spreads only polynomially fast for the other extreme case r≥ n. For a range of suitable values of r, we prove that the process exhibits both phases of the above extremes: It starts with a polynomial growth and eventually transitions from at most cn to n active nodes, for some constant c∈ (0, 1 ), in O(log n) rounds. We observe this behavior also empirically, considering additional global-graph models.
AB - Bootstrap percolation is a classical model for the spread of information in a network. In the round-based version, nodes of an undirected graph become active once at least r neighbors were active in the previous round. We propose the perturbed percolation process: a superposition of two percolation processes on the same node set. One process acts on a local graph with activation threshold 1, the other acts on a global graph with threshold r – representing local and global edges, respectively. We consider grid-like local graphs and expanders as global graphs on n nodes. For the extreme case r= 1, all nodes are active after O(log n) rounds, while the process spreads only polynomially fast for the other extreme case r≥ n. For a range of suitable values of r, we prove that the process exhibits both phases of the above extremes: It starts with a polynomial growth and eventually transitions from at most cn to n active nodes, for some constant c∈ (0, 1 ), in O(log n) rounds. We observe this behavior also empirically, considering additional global-graph models.
KW - Bootstrap percolation
KW - Expanders
KW - Random graphs
KW - Rumor spreading
UR - http://www.scopus.com/inward/record.url?scp=85134336542&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-09993-9_5
DO - 10.1007/978-3-031-09993-9_5
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AN - SCOPUS:85134336542
SN - 9783031099922
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 79
EP - 97
BT - Structural Information and Communication Complexity - 29th International Colloquium, SIROCCO 2022, Proceedings
A2 - Parter, Merav
PB - Springer Science and Business Media Deutschland GmbH
T2 - 29th International Colloquium on Structural Information and Communication Complexity, SIROCCO 2022
Y2 - 27 June 2022 through 29 June 2022
ER -