A Game Theoretic Analysis of Incentives in Content Production and Sharing over Peer-to-Peer Networks

User-generated content can be distributed at a low cost using peer-to-peer (P2P) networks, but the free-rider problem hinders the utilization of P2P networks. In order to achieve an efficient use of P2P networks, we investigate fundamental issues on incentives in content production and sharing using game theory. We build a basic model to analyze non-cooperative outcomes without an incentive scheme and then use different game formulations derived from the basic model to examine five incentive schemes: cooperative, payment, repeated interaction, intervention, and enforced full sharing. The results of this paper show that 1) cooperative peers share all produced content while non-cooperative peers do not share at all without an incentive scheme; 2) a cooperative scheme allows peers to consume more content than non-cooperative outcomes do; 3) a cooperative outcome can be achieved among non-cooperative peers by introducing an incentive scheme based on payment, repeated interaction, or intervention; and 4) enforced full sharing has ambiguous welfare effects on peers. In addition to describing the solutions of different formulations, we discuss enforcement and informational requirements to implement each solution, aiming to offer a guideline for protocol designers when designing incentive schemes for P2P networks.Comment: 31 pages, 3 figures, 1 tabl

A new approach to service provisioning in ATM networks

The authors formulate and solve a problem of allocating resources among competing services differentiated by user traffic characteristics and maximum end-to-end delay. The solution leads to an alternative approach to service provisioning in an ATM network, in which the network offers directly for rent its bandwidth and buffers and users purchase freely resources to meet their desired quality. Users make their decisions based on their own traffic parameters and delay requirements and the network sets prices for those resources. The procedure is iterative in that the network periodically adjusts prices based on monitored user demand, and is decentralized in that only local information is needed for individual users to determine resource requests. The authors derive the network's adjustment scheme and the users' decision rule and establish their optimality. Since the approach does not require the network to know user traffic and delay parameters, it does not require traffic policing on the part of the network

Dynamic Power Allocation Games in Parallel Multiple Access Channels

We analyze the distributed power allocation problem in parallel multiple access channels (MAC) by studying an associated non-cooperative game which admits an exact potential. Even though games of this type have been the subject of considerable study in the literature, we find that the sufficient conditions which ensure uniqueness of Nash equilibrium points typically do not hold in this context. Nonetheless, we show that the parallel MAC game admits a unique equilibrium almost surely, thus establishing an important class of counterexamples where these sufficient conditions are not necessary. Furthermore, if the network's users employ a distributed learning scheme based on the replicator dynamics, we show that they converge to equilibrium from almost any initial condition, even though users only have local information at their disposal.Comment: 18 pages, 4 figures, submitted to Valuetools '1