Title
Location-based Spatial Queries with Data Sharing in Broadcast Environments
Abstract
Spatial query processing is becoming an integral part of many new applications.
Recently, there has been a growing interest in the use of location-based spatial queries
(LBSQs), which refer to a set of spatial queries that retrieve information based on mobile
users’ current locations. Efficient processing of LBSQs is of critical importance with the
ever-increasing deployment and use of mobile technologies.
In this talk, I will show that LBSQs have certain unique characteristics that traditional
spatial query processing in centralized databases does not address. For example, a
significant challenge is presented by wireless broadcasting environments, which often
exhibit high-latency database access. I will present a novel query processing technique
that, while maintaining high scalability and accuracy, manages to reduce the latency
considerably in answering location-based spatial queries. My approach is based on peerto-peer sharing, which enables us to process queries without delay at a mobile host by
using query results cached in its neighboring mobile peers. The experiment results
indicate that my method can reduce the access to the wireless broadcast channel by a
significant amount, for example up to 80% in a dense urban area. This is achieved with
minimal caching at the peers.
Bio
Wei-Shinn Ku is currently an assistant professor in the Department of Computer Science
and Software Engineering at Auburn University. He received the Ph.D. degree in
Computer Science from the University of Southern California (USC) in 2007. He also
obtained the M.S. in Computer Science and the M.S. in Electrical Engineering from USC.
He is a graduate of National Taiwan Normal University. His research interests include
spatial and temporal data management, mobile data management, geographical
information systems, peer-to-peer systems, and network security.