1 research outputs found
Context-sensitive mobile database summarisation
In mobile computing environments, as a result of
the reduced capacity of local storage, it is commonly
not feasible to replicate entire datasets on each mobile
unit. In addition, reliable, secure and economical
access to central servers is not always possible.
Moreover, since mobile computers are designed to be
portable, they are also physically small and thus often
unable to hold or process the large amounts of data
held in centralised databases. As many systems are
only as useful as the data they can process, the support
provided by database and system management
middleware for applications in mobile environments is
an important driver for the uptake of this technology
by application providers and thus also for the wider
use of the technology.
One of the approaches to maximize the available
storage is through the use of database summarisation.
To date, most strategies for reducing data volumes
have used compression techniques that ignore the semantics
of the data. Those that do not use data compression
techniques adopt structural (i.e. data and
use-independent) methods. In this paper, we outline
the special constraints imposed on storing information
in mobile databases and provide a flexible data
summarisation policy. The method works by assigning
a level of priority to each data item through the
setting of a number of parameters. The paper discusses
some policies for setting these parameters and
some implementation strategies.Bedford Park, South Australi