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In cloud computing, IaaS (Infrastructure as a Service) is the foundation of cloud service applications. It enables problems like resource allocation scheduling and bearing capacity to be further optimally solved. Therefore, a genetic optimized IaaS resource optimization evaluation approach is presented. This approach abstractly defines its 7 factors (properties) including usability of server, network performances, load balancing, anomaly notification mechanism, response time support, trusted security and measure payment, and explains quantitative calculation and expressions of each factor. And finally, tested by CloudSim, this approach is indicated to be feasible and effective for resource allocation.
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