Predicting Resource Allocation and Costs for Business Processes in the Cloud

摘要: By moving business processes into the cloud, partners can benefit from lower costs, more flexibility and greater scalability in terms of resources offered by cloud providers. In order to execute a process or part it, owner selects leases feasible while considering different constraints, e.g., Optimizing resource requirements minimizing their costs. this context, utilizing information about models dependencies between tasks help better manage leased resources. paper, we propose novel allocation technique based on execution path process, used assist efficiently leasing computing The comprises three phases, namely prediction, cost estimation. first exploits model metrics attributes predict requires resources, second utilizes prediction for efficient final phase estimates optimizes costs combining pricing provider.