Autonomic resource management through self-organising agent communities

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Description/Abstract

In this paper, we analyse how autonomic resource management can be achieved within a system that lacks centralized information about current system demand and the state of system elements. Rather, regulation of service provision is achieved through local co-adaptation between two groups of system elements, one tasked to autonomously decide which services to offer and the other to consume them in a manner that minimises resource contention. We explore how varying the amount of information stored by agents influences system performance, and demonstrate that when the information capacity of individual agents is limited they self-organise into communities that facilitate the local exchange of relevant information. Such systems are stable enough to allocate resources efficiently and to minimise unnecessary reconfiguration, but also adaptive enough to reconfigure when resource demand changes.