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Multi-agent based peer-to-peer information retrieval systems with concurrent search sessions

In cooperative peer-to-peer information retrieval systems, each node can be considered an intelligent agent and these agents work collectively to provide an information retrieval service. In order to effectively support multiple and concurrent search sessions in the network, we propose two traffic engineering techniques that minimize processing and communication bottlenecks. One is a novel agent control mechanism whose elements include resource selection, local search scheduling, and feedback-based load control. The other is a new two-phase query routing algorithm based on organizational knowledge. Experimental results show that this framework can reduce congestion situations, increase system throughput, and improve considerably the overall system utility.