Conference Paper

Approximating Aggregation Queries in Peer-to-Peer Networks

UC Riverside
DOI: 10.1109/ICDE.2006.23 Conference: Data Engineering, 2006. ICDE '06. Proceedings of the 22nd International Conference on
Source: IEEE Xplore

ABSTRACT Peer-to-peer databases are becoming prevalent on the Internet for distribution and sharing of documents, applications, and other digital media. The problem of answering large scale, ad-hoc analysis queries ― e.g., aggregation queries ― on these databases poses unique challenges. Exact solutions can be time consuming and difficult to implement given the distributed and dynamic nature of peer-to-peer databases. In this paper we present novel sampling-based techniques 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 due to several 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 solutio

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    ABSTRACT: The present peer-to-peer (P2P) content distribution system is based on simple on-demand content discovery technique. This can be improved by implementing additional capabilities namely a mechanism through which peers can register with the network so that they can be continuously informed of new data items, and a means for the peers to advertise their contents. Existing unstructured overlay based systems require complex indexing and routing schemes makes the network less flexible for transient peers. For these applications, we study the alternate continuous query paradigm, which is a best-effort service providing the services. We present a scalable and effective middleware called CQUOS for supporting continuous queries in unstructured overlay networks. CQUOS preserves the simplicity and flexibility of the unstructured P2P network. It has two techniques namely cluster resilient random walk algorithm which is responsible for pro propagating the queries to various regions of the network and dynamic probability-based query registration scheme to ensure that the registrations are well distributed in the overlay. This paper studies the properties of our algorithms through theoretical analysis.

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Nov 19, 2014