Scheduling in the Hybrid Cloud Constrained by Process Mining

Task scheduling in hybrid clouds has been widely used to achieve scalability and security goals for cloud computing. If not well-managed, the challenges of scheduling tasks in a hybrid cloud have the potential to diminish desired benefits due to an extra layer of complexity introduced by two or more cloud deployment models. Apart from efficiency and cost challenge in scheduling tasks across separate clouds, the level of compliance to a set of business rules is a growing concern in cloud computing. This paper proposes a cost-effective model for scheduling tasks over a hybrid cloud with compliance to a given set of business rules. The proposed solution employs the applicative scenario of a hospital billing system with a rule for processing a class of bills only in the private datacenter. Our system successfully employs the Hopcroft Karp algorithm in assigning tasks to appropriate virtual machines and Event Calculus formalisations to monitor compliance. The results of the simulation show the cost-effective use of process mining monitoring to schedule tasks in compliance with business rules in a hybrid cloud.

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