Performance analysis of distributed search in open agent systems

In open multi-agent systems agents need resources provided by other agents but they are not aware of which agents provide the particular resources. Most solutions to this problem are based on a central directory that maintains a mapping between agents and resources. However, such solutions do not scale well since the central directory becomes a bottleneck in terms of both performance and reliability. In this paper, we introduce a different approach: each agent maintains a limited size local cache in which it keeps information about k different resources, that is, for each of k resources, it stores the contact information of one agent that provides it. This creates a directed network of caches. We address the following fundamental problem: how can an agent that needs a particular resource find an agent that provides it by navigating through this network of caches? We propose and analytically compare the performance of three different algorithms for this problem, flooding, teeming and random paths, in terms of three performance measures: the probability to locate the resource, the number of steps and the number of messages to do so. Our analysis is also applicable to distributed search in unstructured peer-to-peer networks.