Abstract
In recent years, immunization strategies have been developed for stopping epidemics in complex-network-like environments. Yet it still remains a challenge for existing strategies to deal with dynamically-evolving networks that contain community structures, though they are ubiquitous in the real world. In this paper, we examine the performances of an autonomy-oriented distributed search strategy for tackling such networks. The strategy is based on the ideas of self-organization and positive feedback from Autonomy-Oriented Computing (AOC). Our experimental results have shown that autonomous entities in this strategy can collectively find and immunize most highly-connected nodes in a dynamic, community-based network within a few steps.
Original language | English |
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Pages (from-to) | 207-226 |
Number of pages | 20 |
Journal | Fundamenta Informaticae |
Volume | 99 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2010 |
Scopus Subject Areas
- Theoretical Computer Science
- Algebra and Number Theory
- Information Systems
- Computational Theory and Mathematics
User-Defined Keywords
- and distributed search
- Autonomy-oriented computing
- complex networks
- immunization strategy
- self-organization