A Clustering Approach to Schedule Workflows to Run on the Cloud
Publish Year: 1395
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ICIKT08_020
تاریخ نمایه سازی: 5 بهمن 1395
Abstract:
Scientific workflows can be considered a useful modeling method to model different scientific applications. Service-oriented computing is an attractive platform for most users to execute these applications in a pay-as-you-go manner. Therefore, scheduling workflows on the cloud as the latest trend in service-oriented computing and meeting the required users’ Quality of Service requirements is an important problem to be tackled. Furthermore, the scheduling algorithms must consider the available multicore processing resources on the commercial Infrastructure as a Service cloud. Hence, considering multicore resources in addition to Quality of Service constraints makes the workflow scheduling problem more challenging to be solved. In this research, a static workflow scheduling algorithm is proposed which considers the available multicore resources on the cloud and attempts to minimize the leasing costs of the processing resources while considering not violating a user-defined deadline. The proposed algorithm uses a clustering technique to divide the workflow into a number of clusters and attempts to combine the clusters in such a way to achieve the algorithms’ main goals. A flexible and extendable scoring approach chooses the best combination available in each step. Extensive simulations reveal a great reduction in the leasing costs of the workflow execution while meeting the user-defined deadline.
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Authors
Arash Deldari
Department of Computer Engineering Ferdowsi university of Mashhad Mashhad, Iran
Mahmoud Naghibzadeh
Department of Computer Engineering Ferdowsi university of Mashhad Mashhad, Iran
Amin Rezaeian
Department of Computer Engineering Ferdowsi university of Mashhad Mashhad, Iran
Hamidreza Abrishami
Department of Computer Engineering Ferdowsi university of Mashhad Mashhad, Iran
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