Processing and Notifying Range Top-k Subscriptions

— We consider how to support a large number of users over a wide-area network whose interests are characterized by range top-k continuous queries. Given an object update, we need to notify users whose top-k results are affected. Simple solutions include using a content-driven network to notify all users whose interest ranges contain the update (ignoring top-k), or using a server to compute only the affected queries and notifying them individually. The former solution generates too much network traffic, while the latter overwhelms the server. We present a geometric framework for the problem that allows us to describe the set of affected queries succinctly with messages that can be efficiently disseminated using content-driven networks. We give fast algorithms to reformulate each update into a set of messages whose number is provably optimal, with or without knowing all user interests. We also present extensions to our solution, including an approximate algorithm that trades off betw...

• Type: Journal
• Year: 2012
• Where: ICDE
• Authors: Albert Yu, Pankaj K. Agarwal, Jun Yang 0001
• Keywords: Approximate Algorithm, Batch Updates, Database, Geometric Framework, ICDE 2012