Deadline and Budget Distribution based Cost- Time Optimization Workflow Scheduling Algorithm for Cloud

computing is a rapidly growing area. Cloud Computing offers utility-oriented IT services to the users worldwide over the internet. As compared to grid computing, the problem of resource management is transformed into resource virtualization and allocations. Effective scheduling is a key concern for the execution of performance driven applications, such as workflows in dynamic and cost-driven environment including clouds. In case of Cloud computing, issues such as resource management and scheduling based on users' QoS constraints are yet to be addressed especially in the context of workflow management systems. In cloud, the users submit their workflows along with some QoS constraints like deadline, budget, trust, reliability etc. for computation. In this paper, we are considering the two constraints: deadline and budget. We propose Deadline and Budget distribution- based Cost-Time Optimization (DBD-CTO) workflow scheduling algorithm that minimizes execution cost while meeting timeframe for delivering results and analyze the behavior of the algorithm.

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