  The volume of data moving through a network increases with new scientific
experiments and simulations. Network bandwidth requirements also increase
proportionally to deliver data within a certain time frame. We observe that a
significant portion of the popular dataset is transferred multiple times to
different users as well as to the same user for various reasons. In-network
data caching for the shared data has shown to reduce the redundant data
transfers and consequently save network traffic volume. In addition, overall
application performance is expected to improve with in-network caching because
access to the locally cached data results in lower latency. This paper shows
how much data was shared over the study period, how much network traffic volume
was consequently saved, and how much the temporary in-network caching increased
the scientific application performance. It also analyzes data access patterns
in applications and the impacts of caching nodes on the regional data
repository. From the results, we observed that the network bandwidth demand was
reduced by nearly a factor of 3 over the study period.
