On Economic and Computational-Efficient Resource Pricing in Large Distributed Systems

There is growing interest in large-scale systems where globally distributed and commoditized resources can be shared and traded, such as peer-to-peer networks, grids, and cloud computing. Users of these systems are rational and maximize their own interest when consuming and contributing shared resources, even if by doing so they affect the overall efficiency of the system. To manage rational users, resource pricing and allocation can provide the necessary incentives for users to behave such that the overall efficiency can be maximized. In this paper, we propose a dynamic pricing mechanism for the allocation of shared resources, and evaluate its performance. In contrast with several existing trading models, our scheme is designed to allocate a request with multiple resource types, such that the user does not have to aggregate different resource types manually. We formally prove the economic properties of our pricing scheme using the mechanism design framework. We perform both theoretical and simulation analysis to evaluate the economic and computational efficiency of the allocation and the scalability of the mechanism. Our simulations are validated against a prototype implementation on PlanetLab.