Abstract

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We study a model of congestible resources, where pricing and scheduling are intertwined. Motivated by the problem of pricing cloud instances, we model a cloud computing service as linked GI/GI/· queuing systems where the provider chooses to offer a fixed pricing service, a dynamic market based service, or a hybrid of both, where jobs can be preempted in the market-based service. Users (jobs), who are heterogeneous in both the value they place on service and their cost for waiting, then choose between the services offered. Combining insights from auction theory with queuing theory we are able to characterize user equilibrium behavior, and show its insensitivity to the precise market design mechanism used. We then provide theoretical and simulation based evidence suggesting that a fixed price typically, though not always, generates a higher expected revenue than the hybrid system for the provider.

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Consider a stochastic loss network, where calls or customer types arrive and have to find a path through the network to a given destination, and where our aim is to maximize the gain (suitably defined) from the network. In general there will be a number of paths available, and when a call arrives the two questions to answer are first, should the call be accepted, and secondly, if it is accepted which route should it take? The answer to the first question is in some sense harder than the second, and all dynamic routing or control policies have some explicit or implicit mechanism for rejecting calls and so answer the question in some way.

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