This paper proposes a composition-based resource allocation approach to cloud infrastructure-as-a-service (IaaS). A number of previous proposals have addressed resource allocation for IaaS services with bandwidth guarantee as the main obstacle to accessing datacenter-based cloud resources. Less focus has been put on utilization of hosting resources, i.e. computing and storage. Shortcomings with these proposals (i) may ensue in a high blocking of IaaS requests and (ii) a less efficient use of datacenter resources, which may impact a provider's revenue. In this research paper, a Two-Phase IaaS resource allocation approach (2P-IaaS) is proposed to address these shortcomings: (i) hosting resources mapping phase, and (ii) connectivity composition phase. This approach adopts a semantic ontology model with its associated reasoning capabilities to represent, discover and assign diverse cloud resources to IaaS requests. Furthermore, the proposed approach utilizes semantic similarity and closeness centrality to define an efficient cloud IaaS topology that connects the assigned resources. In this research, experiments on various sets of IaaS requests show significant advantages when compared with selected benchmarks.