Data centers contain heterogeneous sets of machines. Some machines are faster and some - often the same ones - consume more energy and cost more to operate. The data center coordinator must decide how to allocate these machines to multiple applications of potentially many customers, each of which has different requirements. Given a stream of customer requests for machines, how does the data center provider decide which machines to give to whom and when? The paper proposes new algorithms for a cost-aware provider to maximize its profit as it makes admission and scheduling decisions for the customer requests. The paper shows that it matters which machines are assigned to each customer, especially when the data center is undersaturated.
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