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The peer-to-peer (P2P) networks is heavily used for content distribution applications and are becoming increasingly popular for Internet file sharing. Generally the download of a file can take from minutes up to several hours depending on the level of network congestion or the service capacity fluctuation. In this paper, we consider two major factors that have significant impact on average download time, namely, the spatial heterogeneity of service capacities in different source peers and the temporal fluctuation in service capacity of a single source peer. We prove that both spatial heterogeneity and temporal correlations in service capacity increase the average download time in P2P networks and then analyze a simple, distributed algorithm to minimize the file download time. Here, we have designed a new distributed algorithm namely dynamically distributed parallel periodic switching (D2PS) that effectively removes the negative factors of the existing parallel downloading, chunk based switching, periodic switching, thus minimizing the average download time. There are two schemes (i) Parallel Permanent Connection, and (ii) Parallel Random Periodic Switching in our dynamically distributed parallel periodic switching (D2PS) method. In our Parallel Permanent Connection, the downloader randomly chooses multiple source peers and divides the file randomly into chunks and download happens in parallel for the fixed time slot t and source selection function does not change for that fixed time slot.