Robust implementation of policies using ant-like agents

Abstract

Policy based management is a powerful means for dealing with complex heterogeneous systems. However, the policies are commonly strictly interpreted, and it is tempting to resort to centralized decisions to resolve conflicts. At the same time, swarm intelligence based on "ant like" mobile agents has been shown to be able to deal with challenging optimization and trade-off problems. This paper discusses and demonstrates how policies may be used to govern the behavior of mobile agents to find near optimal solutions for the implementation of a set of potentially conflicting policies in a truly distributed manner. A more dependable/robust system is obtained. The enforcement of the policies is soft in the sense that it is probabilistic and yields a kind of "best effort" implementation. A case study illustrating how ant like mobile agents may implement load distribution and conftict free back-up policies, is presented. © 2003 by Springer Science+Business Media New York.