Mobile devices like PDAs are capable of retrieving information from various types of services. In many cases, the user requests cannot directly be processed by the service providers, if their hosts have limited query capabilities or the query combines data from various sources, which do not collaborate with each other. In this paper, we present a framework for optimizing spatial join queries that belong to this class. We presume that the connection and queries are ad-hoc, there is no mediator available and the services are non-collaborative. We also assume that the services are not willing to share their statistics or indexes with the client. We retrieve statistics dynamically in order to generate a low-cost execution plan, while considering the storage and computational power limitations of the PDA. Since acquiring the statistics causes overhead, we describe an adaptive algorithm that optimizes the overall process of statistics retrieval and query execution. We demonstrate the applicability of our methods with a prototype implementation on a PDA with wireless network access.
|Original language||English (US)|
|Number of pages||19|
|Journal||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|State||Published - 2003|
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)