On the evaluation of flooding-based search strategies in peer-to-peer networks

This paper develops a directed generalized random graphs based analytical modeling framework to compare several variations of the basic flooding search strategy in unstructured decentralized peer-to-peer networks. To validate the model predictions, we designed and implemented a distributed crawler architecture that is able to efficiently capture snapshots of the top-level Gnutella overlay topology. The snapshots are used to obtain simulation results that are used to assess the accuracy of our model. The model predictions are then used to compute system-oriented performance indexes (the average and the coefficient of variation of the number of query messages) as well as user-oriented measures (the probability of finding at least one replica of a resource, the average search time). The trade-off between the optimization of system-oriented measures and the improvement of user-oriented quality indexes is investigated for several variations of the basic flooding strategy suggesting that adding control parameters to the basic flooding mechanism might prove beneficial in this class of systems.