Optimizing cluster formation in super-peer networks via local incentive design

A super-peer based overlay network architecture for peer-to-peer (P2P) systems allows for some nodes, known as the super-peers, that are more resourceendowed than others, to assume a higher share of workload. Ordinary peers are connected to the super-peers and rely on them for their transactional needs. Many criteria for a peer to choose its super-peer have been explored, some of them based on physical proximity, semantic proximity, or by purely random choice. In this paper, we propose an incentive-based criterion that uses semantic similarities between the content interests of the peers and, at the same time, encourages even load distribution across the super-peers. The incentive is achieved via a game theoretic framework that considers each peer as a rational player, allowing stable This research was supported in part by NSF CNS grants 0916179 and 1152320. The game formulation part of the work was presented at the International Workshop on Modeling Analysis and Control of Complex Network (CNET) 2011 at San Fransisco. Aditya Kurve Department of Electrical Engineering The Pennsylvania State University E-mail: [email protected] Christopher Griffin Applied Research Lab The Pennsylvania State University E-mail: [email protected] David J. Miller Department of Electrical Engineering The Pennsylvania State University E-mail: [email protected] George Kesidis Department of Electrical Engineering and Computer Science and Engineering The Pennsylvania State University E-mail: [email protected] Nash equilibria to exist and hence guarantees a fixed point in the strategy space of the peers. This guarantees convergence (assuming static network parameters) to a locally optimal assignment of peers to super-peers with respect to a global cost that approximates the average query resolution time. We also show empirically that the local cost framework that we employ performs closely to (and in some cases better than) a similar scheme based on the formulation of a centralized cost function that requires the peers to know an additional global parameter.