Modeling replication strategies in data grid systems with arbitrary clustered demands
Proceedings of the 3rd international conference on Scalable information systems
A new search mechanism for unstructured peer-to-peer networks
AICT'11 Proceedings of the 2nd international conference on Applied informatics and computing theory
State-based search strategy in unstructured P2P
Future Generation Computer Systems
SMBSRP: a search mechanism based on interest similarity, query relevance and distance prediction
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
| Hi-index | 0.07 |
This paper derives the optimal search time and the optimal search cost that can be achieved in unstructured peer-to-peer networks when the demand pattern exhibits clustering (i.e. file popularities vary across the set of nodes in the network). Clustering in file popularity patterns is evident from measurements on deployed peer-to-peer file sharing networks. In this paper, we provide mechanisms for modeling clustering in file popularity distributions and the consequent non-uniform distribution of file replicas. We derive relations that show the effect of the number of replicas of a file on the search time and on the search cost for a search for that file for the clustered demands case in such networks for both random walk and flooding search mechanisms. The derived relations are used to obtain the optimal search performance for the case of flooding search mechanisms. The potential performance benefit that clustering in demand patterns affords is captured by our results. Interestingly, the performance gains are shown to be independent of whether the search network topology reflects the clustering in file popularity (the optimal file replica distribution to obtain these performance gains, however, does depend on the search network topology)