Peer-to-peer flow detection algorithm has been studied for several years. Port-based classification, regular expression, graphlet and various machine learning based algorithms have been proposed as solutions. Unfortunately, all previous algorithms have been failed in various aspects especially for the encrypted peer-to-peer traffic. In this paper, we present a new algorithm to delivers more effectiveness. We have also prototyped our algorithm and evaluate on a test-bed. The performance evaluation has demonstrated the better effectiveness of our algorithm in comparison to the previous ones.

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Detection and classification of peer-to-peer traffic are still difficult tasks for bandwidth shapers. First, peer-to-peer traffic is not easy to detect, and can be a serious problem. Second, some peer-to-peer applications may be desirable, while some may be undesirable. Hence, different peer-to-peer applications should also be treated differently. The previous work of peer-to-peer traffic detection still faces both problems. So, in this paper, we propose new classification mechanisms to solve the problems. Our proposed solution has been implemented by using JAVA, and experimented on a network test-bed. Experimental results have demonstrated that our extended classification mechanism can improve the peer-to-peer traffic detection and classification.

Named Data Networking (NDN) has been considered as a promising Internet architecture for the future data-centric communication. In particular, NDN over link-layer networks would cut off the overheads of Transmission Control Protocol/Internet Protocol (TCP/IP), and enhance the efficiency of data distribution. However, there are two main unsolved issues for the NDN link-layer, namely broadcast overhead and Maximum Transmission Unit (MTU) mismatch. In this paper, we have therefore designed and implemented an NDN Neighborhood Discovery Protocol, named NDN-NDP, to enable a unicast data transmission over the link-layer. Furthermore, our NDN-NDP has included a negotiation mechanism to fix the MTU mismatch issue. In comparison to previously proposed NDN link-layer technologies, we can fix both MTU mismatch and broadcast overhead problems. Through emulation and experiments on a test-bed, we have also compared our NDN-NDP with the Link-layer Protocol for NDN (NDNLP), which is the most widely deployed NDNLP. From our experiments, NDN-NDP can efficiently fix MTU mismatch and broadcast overhead issue.

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