Splitting a whole large file into some small blocks and distributedly deploying these block replications on severs can improve their application efficiency and meet users' demands.How to split a file

how many replications of a block should be created

and how to deploy these replications become the most critical issures in this field.In this paper

considering client's demands for each block

we introduce block-popularity and present a block deployment strategy according to it

called minimum cost of storing blocks (MCSB)

which can satisfy users' requirement and minimum storage cost.In our strategy

through introducing cost adjustment factors of blocks

not only that lower hot blocks are assured to deploy earlier

but also the practical total storage cost are not exceed than the original case.To maintain the performance of service system

we study resource management methods in-depth among severs with different workloads and propose an adaptive MCSB strategy (AMCSB).We implement the MCSB (and AMCSB) in Hadoop and compare their performance with other related strategies.The experiment results show that MCSB fulfills minimum service cost and shortens average response time

and AMCSB realizes load balance among target servers.