Mechanism Design for Replica Placement in Peer-Assisted Content Delivery Networks with Heterogeneous Behavior Models

Replica placement (RP) is an important technology in content delivery systems to achieve efficient and effective content delivery. Peer-assisted content delivery network (PCDN) has been proposed for simultaneously obtaining the scalability advantage of peer-to-peer networks and the reliability and manageability advantages of content delivery networks. However, the benefits of peer assistance can be severely affected by the self-interested or malicious behaviors of peers. In this research, we utilize mechanism design theory to design robust algorithms for RP in PCDN with the coexistence of altruistic, self-interested, and malicious seeders. Our preliminary results show that RP algorithms that consider peer contributions have better performance in PCDN, in addition, our mechanism incentivizes the contribution of self-interested seeders and further improves the performance of RP in PCDN. We also quantify the impact of malicious behavior on the performance of the mechanism and extend the mechanism to tolerate malicious behaviors.