Peer-to-peer (P2P) based content delivery is fast gaining popularity because of its scalability and low cost. A widely documented problem in P2P networks has been the large number of free riders, users who consume content or resources from the network without sharing it with other users. Academics and practitioners have proposed many solutions, including offering upload rebates. By offering upload rebates (payments to users who share content with others) incentives can be provided for users to host and share content. This research represents one of the first studies of a content distributor’s optimal rebating strategy. We begin by proposing an easy-to-implement constant rebating strategy, where a constant rebate is provided throughout the distribution process. Our results indicate that the optimal rebate decreases with the product demand and number of unselfish users in the network. If future revenue is discounted considerably, then the optimal rebate increases. Motivated by the intuition that a rebate early on plays a more significant role in product diffusion than a rebate in later periods, we present a dynamic rebating strategy, where the content distributor continuously adjusts the rebate. By employing optimal control theory, we find that, for a short-term marketing campaign, the optimal strategy involves a constant high rebate at the beginning, followed by a convex decreasing trajectory that may or may not terminate with zero rebate. In the infinite time horizon case, after the constant rebating period, the optimal rebating trajectory always decreases and converges to zero. Our models and findings serve as a starting point for further study of optimal P2P distribution strategies and also serve to inform content distributors in developing their marketing strategies.
Han, Peng; Hosanager, Kartik; and Tan, Yong-Wah, "Optimal Rebating Strategies in Peer-to-Peer Content Distribution" (2005). ICIS 2005 Proceedings. 54.