The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Deadline Based Resource Provisioningand Scheduling Algorithm for Scientific Workflows on Clouds
Abstract
Cloud computing is the latest distributed computing paradigm and it offers tremendous opportunities to solve large-scale scientific problems. However, it presents various challenges that need to be addressed in order to be efficiently utilized for workflow applications. Although the workflow scheduling problem has been widely studied, there are very few initiatives tailored for cloud environments. Furthermore, the existing works fail to either meet the user's quality of service (QoS) requirements or to incorporate some basic principles of cloud computing such as the elasticity and heterogeneity of the computing resources. This paper proposes a resource provisioning and scheduling strategy for scientific workflows on Infrastructure as a Service (IaaS) clouds. We present an algorithm based on the meta-heuristic optimization technique, particle swarm optimization (PSO), which aims to minimize the overall workflow execution cost while meeting deadline constraints. Our heuristic is evaluated using CloudSim and various well-known scientific workflows of different sizes. The results show that our approach performs better than the current state-of-the-art algorithms.
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Cites
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Self-citationCharacterizing and profiling scientific workflows
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Cloud Computing: Principles And Paradigms
Assistant Professor (SG) Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai, T. N., Geetha, D. P., Raj, D. T. S., & Assistant Professor (SG) Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi, C. (2024) · doi:10.59646/ccp/156 · Cited by 517
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Cited by
Houssein, E. H., Gad, A. G., Wazery, Y. M., & Suganthan, P. N. (2021) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2021.100841 · Cited by 355
Towards workflow scheduling in cloud computing: A comprehensive analysis
Masdari, M., ValiKardan, S., Shahi, Z., & Azar, S. I. (2016) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2016.01.018 · Cited by 266
Cloud Computing Features, Issues, and Challenges: A Big Picture
Puthal, D., Sahoo, B. P. S., Mishra, S., & Swain, S. (2015) · 2015 International Conference on Computational Intelligence and Networks · doi:10.1109/cine.2015.31 · Cited by 256
Metadata
- Authors
- Rodriguez, M. A., & Buyya, R.
- Venue
- IEEE Transactions on Cloud Computing
- Published
- 2014-04-01
- Volume
- 2
- Issue
- 2
- Pages
- 222-235
- ISSN
- 2168-7161 (ISSN-L)
- OpenAlex
- W2088723799
- Cited by
- 686
- References
- 17
- FWCI
- 183.99
- Type
- journal article
- Language
- en
- Open access
- closed
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