Game Based Capacity Allocation for Utility Computing Environments

Utility computing has the potential to greatly increase the efficiency of IT operations by sharing resources across multiple users. This sharing, however, introduces complex problems with regards to pricing and allocating these resources in a way that is fair, easy to implement, and economically efficient. In this paper, we study a queue-based model that attempts to address these issues. Each client / user has a continuous flow of jobs that need to be processed. The service rate each receives, however, is proportional to a bid it submits to the system operator. Assuming that user costs are some function of their average backlogs plus their bid amounts, we use this allocation mechanism to construct an economic game.

Much previous research has shown that these types of allocation games have desirable properties if the cost functions are well-defined and convex over the space of possible outcomes. Because of its queueing interface, however, our model induces functions that do not satisfy the latter, commonly assumed properties. In spite of these complications, we show that the game still has a unique equilibrium and that the system will converge to this point if users iteratively make "best response" updates to their bids. Finally, we discuss some numerical examples, exploring the rate of this convergence as well as some monotonicity properties of the resulting outcomes. Future research will expand this model to broader classes of service and also rigorously investigate its efficiency.