Exploiting locality for scalable information retrieval in peer-to-peer networks

We deploy and compare ISM with a number of other distributed search techniques over static and dynamic environments. Our experiments are performed with real data over Peerware, our middleware simulation infrastructure which is deployed on 75 workstations. Our results indicate that ISM outperforms its competitors and that in some cases it manages to achieve 100% recall rate while using only half of the network resources required by its competitors. Further, its performance is also superior with respect to the total query response time and our algorithm exhibits a learning behavior as nodes acquire more knowledge. Finally ISM works well in dynamic network topologies and in environments with replicated data sources.