Parallel and distributed computation: numerical methods
Parallel and distributed computation: numerical methods
Decentralized regulation of a queue
Management Science
AAMAS '02 Revised Papers from the Workshop on Agent Mediated Electronic Commerce on Agent-Mediated Electronic Commerce IV, Designing Mechanisms and Systems
Market-based Proportional Resource Sharing for Clusters
Market-based Proportional Resource Sharing for Clusters
The utility business model and the future of computing services
IBM Systems Journal
Efficiency Loss in a Network Resource Allocation Game
Mathematics of Operations Research
A framework for uplink power control in cellular radio systems
IEEE Journal on Selected Areas in Communications
A game theoretic formulation of the service provisioning problem in cloud systems
Proceedings of the 20th international conference on World wide web
Socially optimal pricing of cloud computing resources
Proceedings of the 5th International ICST Conference on Performance Evaluation Methodologies and Tools
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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.