.NET Project On  P2p  Replication-Based Performance Improvement.


Peer to peer (P2P) databases is getting to be prevalent on the Internet for distribution and sharing of documents, applications and other digital media. The issue of answering large-scale ad hoc analysis queries, for example, aggregation queries, on these databases possess unique challenges. Exact solutions can be time-consuming and difficult to implement, given the distributed and dynamic nature of P2P databases. We display novel sampling-based strategies for approximate answering of ad hoc aggregation queries in such databases.

Computing a high quality random sample of the database efficiently in the P2P environment is complicated because of a few factors: the data is distributed(usually in uneven quantities)across many peers, within each peer, the data is often highly correlated and, moreover, even collecting a random sample of the peers is difficult to accomplish. To counter these problems, we have developed an adaptive two-phase sampling approach based on random walks of the P2P graph, as well as block-level sampling techniques. We present extensive experimental evaluations to demonstrate the feasibility of our proposed solution.

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