OPNET PROJECTS TOPICS
A study of user incentive mechanism in named data networking
Various named data networking (NDN) functions facilitate P2P content distribution, but the user incentive mechanism is missing. In this paper, we study the user incentive mechanism in NDN, particularly the information gathering, i.e., collecting user contribution information to be used to evaluate and reciprocate users, through simulations based on real Bit-Torrent trace. We found that two specific users are matched repeatedly even though the user matching is driven by NDN because the name-based routing naturally realizes the communication localization. As a result, even based only on their personal experiences, users can handle around 81% of content requests with the contribution information about content requesters.
Due to the same reason, simple opportunistic exchange (that allows users to share their experiences when they upload a requested content) enables users to handle around 97% of content requests with the contribution information about content requesters. The publish/subscribe paradigm of NDN can also be exploited to enable users to share their experiences, i.e., by publishing their transaction histories. However, considering a huge number of P2P users and contents, this approach is likely to burden NDN routers with high processing and storage overheads.