The increasing maturity of cloud technologies produce increasing number of cloud computing resource vendors and services. More choices for cloud adopters also bring more complexities and challenges in selecting cloud products. Different application types (e.g., concurrent/communication/computing/data intensive )may have distinct requirements, cost constraints and applicationspecified features (e.g., data volume size/data transfer velocity, communication/access frequency, computing intension). Meanwhile, different cloud platforms have their unique strengths and weaknesses in computational capacities, technologies, and pricing rules and strategies (e.g., on demand/reserved/biding mode). The match between the diverse cloud capacities provisions and application requirements require systematic and complex knowledge for selecting cloud platform. It is not an easy task to make a wise decision for the novices and even for experienced cloud users. This research discusses the general measurement criteria, cost evaluation models and platform/configuration selecting methods for cloud computing. We also demonstrate a cloud platform adoptio advisory tool as part of the ESIP Testbed projects. The web based advisory tool can: 1) generate feasible cloud configuration solution according to user inputs; 2) calculate and visually compare the cost and capacities of the solutions; 3) make recommendation basedembedded evaluation mechanism.
 | Name: Kai Liu Organization(s): GMU Email: [email protected] |