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Today, many commercial and private cloud computing providers offer resources for leasing under the infrastructure as a service (IaaS) paradigm. Although an abundance of mechanisms already facilitate the lease and use of single infrastructure resources, to complete multi-job workloads IaaS users still need to select adequate provisioning and allocation policies to instantiate resources and map computational jobs to them. While such policies have been studied in the past, no experimental investigation in the context of clouds currently exists that considers them jointly. In this paper we present a comprehensive and empirical performance-cost analysis of provisioning and allocation policies in IaaS clouds. We first introduce a taxonomy of both types of policies, based on the type of information used in the decision process, and map to this taxonomy eight provisioning and four allocation policies. Then, we analyze the performance and cost of these policies through experimentation in three clouds, including Amazon EC2. We show that policies that dynamically provision and/or allocate resources can achieve better performance and cost. Finally, we also look at the interplay between provisioning and allocation, for which we show preliminary results.