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This paper studies the problem of procuring diverse resources in a forwardmarket to cover a set $\bf{E}$ of uncertain demand signals $\bf{e}$. Weconsider two scenarios: (a) $\bf{e}$ is revealed all at once by an oracle (b)$\bf{e}$ reveals itself causally. Each scenario induces an optimal procurementcost. The ratio between these two costs is defined as the {\em price ofcausality}. It captures the additional cost of not knowing the future values ofthe uncertain demand signal. We consider two application contexts: procuringenergy reserves from a forward capacity market, and purchasing virtual machineinstances from a cloud service. An upper bound on the price of causality isobtained, and the exact price of causality is computed for some special cases.The algorithmic basis for all these computations is set containment linearprogramming. A mechanism is proposed to allocate the procurement cost toconsumers who in aggregate produce the demand signal. We show that the proposedcost allocation is fair, budget-balanced, and respects the cost-causationprinciple. The results are validated through numerical simulations.

Optimal Resource Procurement and the Price of Causality