  Grid environment is a service oriented infrastructure in which many
heterogeneous resources participate to provide the high performance
computation. One of the bug issues in the grid environment is the vagueness and
uncertainty between advertised resources and requested resources. Furthermore,
in an environment such as grid dynamicity is considered as a crucial issue
which must be dealt with. Classical rough set have been used to deal with the
uncertainty and vagueness. But it can just be used on the static systems and
can not support dynamicity in a system. In this work we propose a solution,
called Dynamic Rough Set Resource Discovery (DRSRD), for dealing with cases of
vagueness and uncertainty problems based on Dynamic rough set theory which
considers dynamic features in this environment. In this way, requested resource
properties have a weight as priority according to which resource matchmaking
and ranking process is done. We also report the result of the solution obtained
from the simulation in GridSim simulator. The comparison has been made between
DRSRD, classical rough set theory based algorithm, and UDDI and OWL S combined
algorithm. DRSRD shows much better precision for the cases with vagueness and
uncertainty in a dynamic system such as the grid rather than the classical
rough set theory based algorithm, and UDDI and OWL S combined algorithm.
