Design of a Scheduling Approach for Budget-Deadline Constrained Applications in Heterogeneous Clouds

The notion of seemingly infinite resources and the dynamic provisioning of these resources on rental premise fascinated the execution of scientific applications in the cloud. The scheduling of the workflows under the utility model is always constrained to some QoS (Quality of Service). Generally, time and cost are considered to be the most important parameters. Scheduling of workflows becomes more challenging when both the time and cost factors are considered simultaneously. Therefore, most of the algorithms have been designed considering either time or cost factor. Hence, to handle the scheduling problem, in this paper, a novel heuristic algorithm named SDBL (Sub-deadline and Budget level) workflow scheduling algorithm for the heterogeneous cloud has been proposed. The proposed methodology effectively utilizes the deadline and budget constrained workflows. The novel strategy of distributing deadline as the level deadline (subdeadline) to each level of workflow and the mechanism of budget distribution to every individual task satisfies the given constraints and results the exceptional performance of SDBL. SDBL strives to produce a feasible schedule meeting the deadline and the budget constraints. The PSR (Planning Success Rate) is utilized to show the efficiency of the proposed algorithm. For simulation, real workflows were exploited over the methodologies such as SDBL (Sub-deadline and budget level workflow scheduling algorithm), BDSD, BHEFT (Budget Constraint Heterogeneous Earliest Finish Time), and HBCS (Heterogeneous Budget Constrained Scheduling). The comprehensive experimental evaluation demonstrates the effectiveness of the proposed methodology in terms of higher PSR in most cases.