Stanford University

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Optimal Algorithmic Pricing in the Cloud Computing Market

Researchers

Abstract

I study selling mechanisms by a monopolist for imperfectly durable, interruptible and homogeneous goods, having the infrastructure as a service public cloud computing market as a motivating example. Buyers have private information about their types/valuations. I find that a randomized pricing mechanism that includes the risk of interruption of the service (e.g., virtual machine) can be both optimal and welfare improving in comparison to deterministic pricing where the risk of interruption is absent: randomized pricing overcomes the “market for lemons” failure and leads trade expansion. High type buyers cross-subsidize low type buyers contributing to the reduction of inequality in the online ecosystem.

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Stanford University