Optimizing access cost for top-k queries over Web sources: a unified cost-based approach

We study the problem of supporting ranked queries in middleware environments, where queries are evaluated over multiple sources. In particular, we study Web middleware scenarios, querying over various Web sources. To motivate, consider a Web "travel agent" scenario for finding restaurants and hotels. (We use this real scenario as "benchmark" queries for experiments as well). In particular, how to access sources with different capabilities and costs, to answer queries efficiently? As our Web middleware coordinates various sources, each source access incurs network communication and server computation. This paper aims at optimizing such access, costs-which dominate the overall query processing (like I/O in relational DBMS).