Optimize the Cost of Resources in Federated Cloud by Collaborated Resource Provisioning and Most Cost-effective Collated Providers Resource First Algorithm

Abstract

Cloud Computing works as the best solution for providing many of its services for cloud consumer agents with different requests for huge computational VM's with large storage capacity. The instance requests of cloud consumers will dynamically change as per their usage of application requirements with the demand for business growth, and singlevendor cloud becomes a constraint to satisfy these needs of the cloud consumers. Federated Cloud can contribute its solution approaches to meet these dynamic needs of cloud consumer requests of resource instances. The interoperability of clouds was made realistic with cloud federation. This paper provides an optimized solution approach where a set of collaborated cloud providers will provide services to satisfy consumer agents multiple requests. It presents the two-phase collaborated resource provisioning (CCRP) approach and Most Cost-Effective Collated Providers Resources First (MCECPRF) algorithm. The algorithm’s efficiency has been tested with specific data set for optimizing the cost for cloud consumer agents and analyzes the cancellation of requests, decision time for provisioning for different VM configurations within specific time slots.