Adaptive Data Replication in Distributed Systems

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The University of Illinois at Chicago and the University of Maryland at Baltimore County collaborate on this project motivated by the tremendous growth of the Internet and the World-Wide-Web (WWW). Adaptive replication is an approach for improving performance, response time, and access cost in distributed database systems in general, and Internet/WWW in particular. Adaptive replication is a generalization of the principle of caching. In adaptive replication the number of copies of an object, the location of these copies, and which updates are propagated to each copy, change dynamically depending on a given cost function. The project establishes the fundamental principles of adaptive replication in distributed database systems, and it develops, implements and analyzes a system for adaptive replication of objects. The system consists of a set of algorithms to be used for various cost functions. For the analysis the investigators are building a simulation testbed in which the user defines the network, selects a replication algorithm, selects a cost model, and an access pattern at each computer. The system enables comparison among the various adaptive and static replication algorithms. The project will improve the understanding, cost, and performance of distributed systems and distributed databases, and it can lead to a more efficient Internet and World-Wide-Web.