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.