A Particle Swarm Optimization Approach for Workflow Scheduling on Cloud Resources Priced by CPU Frequency

Thiago A L Genez; Ilia Pietri; Rizos Sakellariou; Luiz F. Bittencourt; Edmundo R M Madeira

doi:10.1109/UCC.2015.40

A Particle Swarm Optimization Approach for Workflow Scheduling on Cloud Resources Priced by CPU Frequency

Thiago A L Genez, Ilia Pietri, Rizos Sakellariou, Luiz F. Bittencourt, Edmundo R M Madeira

Universidade Estadual de Campinas

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper, we propose a procedure based on Particle Swarm Optimization (PSO) to guide the user in splitting an amount of CPU capacity (sum of frequencies) among a fixed number of resources in order to minimize the execution time (makespan) of the workflow. The proposed procedure was evaluated and compared with a naive approach, which selects only identical CPU frequency configurations for resources. Simulation results show that, by keeping the overall amount of provisioned CPU frequency constant, the proposed PSO-based approach was able to reduce the makespan of the workflow by carefully selecting different CPU frequencies for resources.

Original language	English
Title of host publication	Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015
Publisher	IEEE
Pages	237-241
Number of pages	5
ISBN (Electronic)	9780769556970
DOIs	https://doi.org/10.1109/UCC.2015.40
Publication status	Published - 10 Mar 2016
Event	8th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2015 - Limassol, Cyprus Duration: 7 Dec 2015 → 10 Dec 2015

Conference

Conference	8th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2015
Country/Territory	Cyprus
City	Limassol
Period	7/12/15 → 10/12/15

Keywords

Cloud computing
PSO
workflow scheduling

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10.1109/UCC.2015.40

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Genez, T. A. L., Pietri, I., Sakellariou, R., Bittencourt, L. F., & Madeira, E. R. M. (2016). A Particle Swarm Optimization Approach for Workflow Scheduling on Cloud Resources Priced by CPU Frequency. In Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015 (pp. 237-241). Article 7431415 IEEE. https://doi.org/10.1109/UCC.2015.40

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title = "A Particle Swarm Optimization Approach for Workflow Scheduling on Cloud Resources Priced by CPU Frequency",

abstract = "In this paper, we propose a procedure based on Particle Swarm Optimization (PSO) to guide the user in splitting an amount of CPU capacity (sum of frequencies) among a fixed number of resources in order to minimize the execution time (makespan) of the workflow. The proposed procedure was evaluated and compared with a naive approach, which selects only identical CPU frequency configurations for resources. Simulation results show that, by keeping the overall amount of provisioned CPU frequency constant, the proposed PSO-based approach was able to reduce the makespan of the workflow by carefully selecting different CPU frequencies for resources.",

keywords = "Cloud computing, PSO, workflow scheduling",

author = "Genez, {Thiago A L} and Ilia Pietri and Rizos Sakellariou and Bittencourt, {Luiz F.} and Madeira, {Edmundo R M}",

year = "2016",

month = mar,

day = "10",

doi = "10.1109/UCC.2015.40",

language = "English",

pages = "237--241",

booktitle = "Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015",

publisher = "IEEE",

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note = "8th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2015 ; Conference date: 07-12-2015 Through 10-12-2015",

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Genez, TAL, Pietri, I, Sakellariou, R, Bittencourt, LF & Madeira, ERM 2016, A Particle Swarm Optimization Approach for Workflow Scheduling on Cloud Resources Priced by CPU Frequency. in Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015., 7431415, IEEE, pp. 237-241, 8th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2015, Limassol, Cyprus, 7/12/15. https://doi.org/10.1109/UCC.2015.40

A Particle Swarm Optimization Approach for Workflow Scheduling on Cloud Resources Priced by CPU Frequency. / Genez, Thiago A L; Pietri, Ilia; Sakellariou, Rizos et al.
Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015. IEEE, 2016. p. 237-241 7431415.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - A Particle Swarm Optimization Approach for Workflow Scheduling on Cloud Resources Priced by CPU Frequency

AU - Genez, Thiago A L

AU - Pietri, Ilia

AU - Sakellariou, Rizos

AU - Bittencourt, Luiz F.

AU - Madeira, Edmundo R M

PY - 2016/3/10

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N2 - In this paper, we propose a procedure based on Particle Swarm Optimization (PSO) to guide the user in splitting an amount of CPU capacity (sum of frequencies) among a fixed number of resources in order to minimize the execution time (makespan) of the workflow. The proposed procedure was evaluated and compared with a naive approach, which selects only identical CPU frequency configurations for resources. Simulation results show that, by keeping the overall amount of provisioned CPU frequency constant, the proposed PSO-based approach was able to reduce the makespan of the workflow by carefully selecting different CPU frequencies for resources.

AB - In this paper, we propose a procedure based on Particle Swarm Optimization (PSO) to guide the user in splitting an amount of CPU capacity (sum of frequencies) among a fixed number of resources in order to minimize the execution time (makespan) of the workflow. The proposed procedure was evaluated and compared with a naive approach, which selects only identical CPU frequency configurations for resources. Simulation results show that, by keeping the overall amount of provisioned CPU frequency constant, the proposed PSO-based approach was able to reduce the makespan of the workflow by carefully selecting different CPU frequencies for resources.

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BT - Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015

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ER -

A Particle Swarm Optimization Approach for Workflow Scheduling on Cloud Resources Priced by CPU Frequency

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