Aggregate Query Processing using Random walk approach in Dynamic Environment

Peer-to-peer (P2P) network is increasingly becoming popular because it offers oppor¬tunities for real-time communication, ad-hoc collaboration and information sharing in a large-scale distributed environment. Peer-to-peer computing is defined as the sharing of computer resources and information through direct exchangeThe advantages of the P2P systems are multi-dimensional; they improve scalability by enabling direct and real-time sharing of services and information; enable knowledge sharing by aggregating information and resources from nodes that are located on geographically distributed and potentially heterogeneous platforms; and, provide high availability by eliminating the need for a single centralized component. 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. 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.