Abstract: The overall service performance of I/O intensive
system depends mainly on workload on its storage system. In
heterogeneous storage environment where storage elements from
different vendors with different capacity and performance are put
together, workload should be distributed according to storage
capability. This paper addresses data placement issue in short video
sharing website. Workload contributed by a video is estimated by the
number of views and life time span of existing videos in same
category. Experiment was conducted on 42,000 video titles in six
weeks. Result showed that the proposed algorithm distributed
workload and maintained balance better than round robin and random
algorithms.