Increasingly infrastructure providers are supplying the cloud marketplace with storage and on-demand compute\r\nresources to host cloud applications. From an application user�s point of view, it is desirable to identify the most\r\nappropriate set of available resources on which to execute an application. Resource choice can be complex and may\r\ninvolve comparing available hardware specifications, operating systems, value-added services (such as network\r\nconfiguration or data replication) and operating costs (such as hosting cost and data throughput). Providers� cost\r\nmodels often change and new commodity cost models (such as spot pricing) can offer significant savings. In this\r\npaper, a software abstraction layer is used to discover the most appropriate infrastructure resources for a given\r\napplication, by applying a two-phase constraints-based approach to a multi-provider cloud environment. In the first\r\nphase, a set of possible infrastructure resources is identified for the application. In the second phase, a suitable\r\nheuristic is used to select the most appropriate resources from the initial set. For some applications a cost-based\r\nheuristic may be most appropriate; for others a performance-based heuristic may be of greater relevance. A financial\r\nservices application and a high performance computing application are used to illustrate the execution of the\r\nproposed resource discovery mechanism. The experimental results show that the proposed model can dynamically\r\nselect appropriate resouces for an application�s requirements.
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