A fast algorithm for subspace clustering by pattern similarity
Haixun Wang, Fang Chu, et al.
SSDBM 2004
Location-based spatial queries (LBSQs) refer to spatial queries whose answers rely on the location of the inquirer. Efficient processing of LBSQs is of critical Importance with the ever-increasing deployment and use of mobile technologies. We show that LBSQs have certain unique characteristics that the traditional spatial query processing in centralized databases does not address. For example, a significant challenge is presented by wireless broadcasting environments, which have excellent scalability but often exhibit high-latency database access. In this paper, we present a novel query processing technique that, though maintaining high scalability and accuracy, manages to reduce the latency considerably in answering LBSQs. Our approach is based on peer-to-peer sharing, which enables us to process queries without delay at a mobile host by using query results cached in its neighboring mobile peers. We demonstrate the feasibility of our approach through a probabilistic analysis, and we illustrate the appeal of our technique through extensive simulation results. © 2008 IEEE.
Haixun Wang, Fang Chu, et al.
SSDBM 2004
Haixun Wang, Jian Pei, et al.
KDD 2005
Wei Peng, Chang-Shing Perng, et al.
KDD 2007
Qi Zhao, Mitsunori Ogihara, et al.
SIGMOD/PODS/ 2006