A mechanism for pricing and resource allocation in peer-to-peer networks

In this study, we design a pricing and allocation mechanism for a peer-to-peer (P2P) network that allows users in a firm to effectively share their computing resources. This mechanism allows tasks (incoming jobs) to be allocated to resources (participating peers) in an organization in a decentralized manner. The base case of our P2P mechanism derives the optimal transfer price that maximizes the net value, which is characterized as the difference between the expected gross value of the jobs and the expected delay cost, for the peers in the network. The optimal price for executing any job at a peer location is essentially equal to the marginal delay cost it imposes on all current jobs at that node. With this pricing scheme, no individual user has an incentive to overutilize shared resources, thereby avoiding the ‘Tragedy of the Commons’ for the P2P network. Our model builds on the classical Mendelson (1985) study that was one of the first to look at the control and management issues related to a single server computer system. In this study, we model transfer pricing for a multiple server environment of a P2P network. The original Mendelson (1985) model thus becomes a special single server case of our general model. Our basic model is extended to incorporate situations where the peers have queue length constraints, which may be used for providing Quality of Service (QoS) guarantees to users. We then perform numerical computations that illustrate the effects of job arrivals on prices and job allocations at the individual servers. There is an enormous potential for P2P based technologies to help organizations manage their computer resources effectively. Therefore, we believe that this study contributes to an important area for information systems (IS) research.