HJSA: A Hierarchical Job Scheduling Algorithm for Cost Optimization

Cloud is emerged day-by-day in the distributed environment and facing innumerable tackles, one amongst is Scheduling. Job scheduling is a vital task in cloud computing as the customer has to pay for used resources depends on the time and cost. In existence, scheduling algorithms are recognized in the job length and the speed of the resources. The job execution in the cloud necessities multiple nodes to execute the single job. This approach is not sufficient to predict the optimal cost in the multi-node execution platform. The cost of the network transmission is also not considered for scheduling cost. To drown these complications, a Hierarchical Job Scheduling Algorithm (HJSA) is proposed. The major objective of the proposed work is to schedule the jobs with respect to the parameters of transmission cost, transfer cost, and execution cost of each job. Subsequently, it also predicts the multiple resources for job completion at the specific time. This is considered as the deadline of the workflow that provided by the customer in the cloud environment. To drown the deadline, the jobs are allocated using application splitting jobs to the small level task. A novel computational algorithm is introduced for predicting the optimum resources to complete the job with the defined cost and time. The experimental analysis representing the lower time and cost, and also the higher reliability and throughput than the existing techniques.