Approximating resource provisioning cost in cloud Computing using reduced scenario set obtained from Fast Forward Selection algorithm

One of the recent advances in the information technology is the emergence of cloud computing. It is a style of computing in which IT-related capabilities are provided “as a service”. Virtualization technologies have been instrumental in growth of cloud computing technologies. In an environment where multiple vendors providing cloud services having different pricing schemes capacity planning is a major concern for any consumer using cloud services. Cloud computing provides a pay-as-you go model where the consumer pays only for the used resources. In such an environment, resource provisioning plays a major role in minimizing the consumers cost. For efficient resource provisioning various algorithms and techniques based on linear programming are applied. Optimal Cloud Resource Provisioning, Max-reservation and No-reservation are three policies that are considered in the paper. Cost calculated using the above mentioned algorithms are compared with the approximated cost calculated with lower number of scenarios. This is done to test the accuracy of scenario reduction techniques.