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Reverse preferential spread in complex networks
Hiroshi Toyoizumi1, Seiichi Tani, Naoto Miyoshi
1Waseda University, Nishi-waseda 1-6-1, Shinjuku, Tokyo JP-169-8050, Japan.
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|September 26, 2012
Summary
Reverse preferential spread, distributing information inversely proportional to node degree, proves more efficient than other methods in large networks. This approach maximizes information dissemination, achieving logistic growth independent of network structure.
Area of Science:
- Network Science
- Information Dissemination Dynamics
Background:
- Large-degree nodes, while influential, can impede information spread due to redundant attempts.
- Inefficient information diffusion can occur in complex networks.
Purpose of the Study:
- To investigate the efficiency of reverse preferential spread for information dissemination.
- To compare reverse preferential spread with other weight-based spread mechanisms.
Main Methods:
- Theoretical analysis of information spread in large, uncorrelated networks.
- Mathematical modeling of reverse preferential spread dynamics.
Main Results:
- Reverse preferential spread demonstrates an advantage over other mechanisms.
- The mean number of nodes reached follows logistic growth, independent of degree distribution.
- This method provides an upper bound for information spread efficiency in weight-based mechanisms.
Conclusions:
- Reverse preferential spread is a highly effective strategy for maximizing information dissemination in large networks.
- The logistic growth pattern highlights the predictable and efficient nature of this spread mechanism.
- Network structure, specifically degree distribution, does not limit the efficiency of reverse preferential spread.
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