Optimization of Cost and Meeting Deadline in Scientific Workflow

Ruchita P. Pingale; Smita S. Patel

doi:https://doi.org/10.14445/22315381/IJETT-V48P239

Research Article | Open Access | Download PDF

Volume 48 | Number 2 | Year 2017 | Article Id. IJETT-V48P239 | DOI : https://doi.org/10.14445/22315381/IJETT-V48P239

Optimization of Cost and Meeting Deadline in Scientific Workflow

Ruchita P. Pingale, Smita S. Patel

Citation :

Ruchita P. Pingale, Smita S. Patel, "Optimization of Cost and Meeting Deadline in Scientific Workflow," International Journal of Engineering Trends and Technology (IJETT), vol. 48, no. 2, pp. 219-223, 2017. Crossref, https://doi.org/10.14445/22315381/IJETT-V48P239

Abstract

Cloud computing is booming technology in the area of information technology. Nowadays, the clouds are known as the global storage and used by many companies, schools, websites etc. The elasticity property of the cloud makes it a suitable platform for the execution of the scientific workflow with the deadline constraint. Resource required for the application is dynamically allocated. The existing algorithms in the area of the scientific workflow either try to minimize the cost or focus on minimizing execution time while trying to meet the application deadline. Also, the existing algorithm considers only one data Centre of the cloud. To increase the performance of scheduling process within the deadline we proposed the enhancement to the EIPR algorithm which uses the idle time slots for providing resource and the budget surplus to replicate the task. Replication uses another data Centre for scheduling process. However, the soft deadline is considered for the process. The working of EIPR algorithm checked on the experiments like montage (25, 50- this is the no of task included in the graph). This shows the implemented algorithm (EIPR) is able to minimize the cost and the execution time of scheduling process in scientific workflow.

Keywords

Scientific Workflow, Soft Deadline, EIPR, Data Centre.

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