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In contemporary period huge amount of data will be stored on cloud server, these types of data is referred as Big-Data. Big data computing is a complicated issue for broadcasters and engineers because they are dealing with datasets of petabytes in the cloud. To manage process and broadcast these massive data has increased drastically. Here we propose an approach to broadcast the data by large chunks to group of nodes that can reduce the maximum completion time. Here we model a Lock Step Broadcast Tree (LSBT) which will define an upload bandwidth(r) and each node capacity(C) at c/r per children. After these data sets divided into chunks, and are broadcasted in a pipeline manner. In homogeneous network environment the capabilities of each node is C, and uplink rate r which gives less maximum completion time. In heterogeneous networks capabilities C1, C2...Cn, so optimal uplink rate r will be calculated by O (nlog 2 n) algorithm there after we construct a LSBT. Finally our results show less computational complexity and less maximum completion time over other broadcasting techniques.
P. Naresh (Sat,) studied this question.