Optimal incentive-compatible priority pricing for the M/M/1 queue
Operations Research
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
A taxonomy of market-based resource management systems for utility-driven cluster computing
Software—Practice & Experience
Pricing Communication Networks: Economics, Technology and Modelling (Wiley Interscience Series in Systems and Optimization)
Network optimization and control
Foundations and Trends® in Networking
Amdahl's Law in the Multicore Era
Computer
Game based capacity allocation for utility computing environments
Proceedings of the 3rd International Conference on Performance Evaluation Methodologies and Tools
Communications of the ACM
Ex-post efficient resource allocation for Self-organizing Cloud
Computers and Electrical Engineering
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The cloud computing paradigm offers easily accessible computing resources of variable size and capabilities. We consider a cloud-computing facility that provides simultaneous service to a heterogeneous, time-varying population of users, each associated with a distinct job. Both the completion time, as well as the user's utility, may depend on the amount of computing resources applied to the job. In this paper, we focus on the objective of maximizing the long-term social surplus, which comprises of the aggregate utility of executed jobs minus load-dependent operating expenses. Our problem formulation relies on basic notions of welfare economics, augmented by relevant queueing aspects. We first analyze the centralized setting, where an omniscient controller may regulate admission and resource allocation to each arriving job based on its individual type. Under appropriate convexity assumptions on the operating costs and individual utilities, we establish existence and uniqueness of the social optimum. We proceed to show that the social optimum may be induced by a single per-unit price, which charges a fixed amount per unit time and resource from all users.