A Two Stage Deadline Aware Workflow Scheduling Strategy for Load Balancing in Cloud Environment
DOI:
https://doi.org/10.54938/ijemdcsai.2026.05.1.603Keywords:
Cloud Environment, Cloud computing Max-Min algorithm, two-stage deadline-aware, schedulingAbstract
Cloud computing enables on-demand access to shared computational resources, but effective load balancing remains a major challenge in heterogeneous environments. Scheduling must be performed quickly while optimizing resource utilization and meeting workflow deadlines, a task complicated by job dependencies, dynamic workloads, and variable execution times. The commonly used Max-Min scheduling algorithm assigns larger tasks to faster resources; however, it often produces a high makespan and poor resource utilization when long tasks dominate the workload. To address this limitation, this study proposes a two-stage deadline-aware workflow scheduling strategy designed to reduce makespan and prevent deadline violations. The proposed method was evaluated across twelve scenarios involving three different workflow types and compared with a benchmark approach. Experimental results show that the proposed strategy consistently achieves a lower makespan than the traditional Max-Min algorithm, demonstrating improved efficiency and performance in cloud computing environments.
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