Following the emergence of peer-to-peer (P2P) applications, millions of computer users have used P2P systems to search for desired content. P2P traffic is known to be highly redundant because of its inherent self-scaling characteristics, which means that file sharing is performed more efficiently when more users exchange the same content. To remove redundant P2P traffic, we have proposed a method to control the P2P traffic through a packet-level data cache that acts as a network function at the edge of the Internet service provider (ISP) networks [1]. However, our previous method involves high levels of memory consumption. Software-defined networking (SON) and network functions virtualization (NFV) are representative trends in network soft-warization that may lower the barrier to deployment of network management functions that are considered to be useful but are difficult to actually implement and deploy. In this paper, we propose a new flow classification for P2P that uses a queue Bloom filter (QBF) to reduce the memory consumption of the P2P cache. The QBF is a time series queue that manages Bloom filters and it can remove inserted Bloom filter elements without generating false positives. If the router can confirm that P2P flows are carrying duplicate contents using QBF, it then begins to cache the duplicate content. Our analysis shows that the proposed method reduces memory consumption to 67% and improves the P2P cache hit ratio by 4% when compared with the previous approach, while its performance in removing redundancy from the P2P traffic is degraded by only 14% . In addition, we discuss the implementation and deployment of the proposed system at the edge routers of ISP networks by applying SON and NFV.