  Data grid replication is an effective method to achieve efficient and fault
tolerant data access while reducing access latency and bandwidth consumption in
grids. Since we have storage limitation, a replica should be created in the
best site. Through evaluation of previously suggested algorithms, we understand
that by blind creation of replications on different sites after each demand, we
may be able to improve algorithm regarding response time. In practice, however,
most of the created replications will never be used and existing resources in
Grid will be wasted through the creation of unused replications. In this paper,
we propose a new dynamic replication algorithm called Predictive Fuzzy
Replication (PFR). PFR not only redefines the Balanced Ant Colony Optimization
(BACO) algorithm, which is used for job scheduling in grids, but also uses it
for replication in appropriate sites in the data grid. The new algorithm
considers the history usage of files, files size, the level of the sites and
free available space for replication and tries to predict future needs and pre
replicates them in the resources that are more suitable or decides which
replica should be deleted if there is not enough space for replicating. This
algorithm considers the related files of the replicated file and replicates
them considering their own history. PFR acts more efficiently than Cascading
method, which is one of the algorithms in optimized use of existing replicas.
