A biased random-key genetic algorithm for the cloud resource management problem

Leonard Heilig; Eduardo Lalla-Ruiz; Stefan Voß

doi:10.1007/978-3-319-16468-7_1

A biased random-key genetic algorithm for the cloud resource management problem

Leonard Heilig^*, Eduardo Lalla-Ruiz, Stefan Voß

^*Corresponding author for this work

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

4 Citations (Scopus)

Abstract

Flexible use options and associated cost savings of cloud computing are increasingly attracting the interest from both researchers and practitioners. Since cloud providers offer various cloud services in different forms, there is a large potential of optimizing the selection of those services from the consumer perspective. In this paper, we address the Cloud Resource Management Problem that is a recent optimization problem aimed at reducing the payment cost and the execution time of consumer applications. In the related literature, there is one approach that successfully addresses this problem based on a Greedy Randomized Adaptive Search Procedure. Due to the fact that consumers require fast and high-quality solutions to economically automate cloud resource management and deployment processes, we propose an efficient Biased Random-Key Genetic Algorithm. The computational experiments over a benchmark suite generated based on real cloud market offerings indicate that the performance of our approach outperforms the approaches proposed in the literature.

Original language	English
Title of host publication	Evolutionary Computation in Combinatorial Optimization - 15th European Conference, EvoCOP 2015, Proceedings
Editors	Gabriela Ochoa, Francisco Chicano
Publisher	Springer
Pages	1-12
Number of pages	12
ISBN (Electronic)	978-3-319-16468-7
ISBN (Print)	978-3-319-16467-0
DOIs	https://doi.org/10.1007/978-3-319-16468-7_1
Publication status	Published - 1 Jan 2015
Externally published	Yes
Event	15th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2015 - National Museum, Copenhagen, Denmark Duration: 8 Apr 2015 → 10 Apr 2015 Conference number: 15 http://www.evostar.org/2015/cfp_evocop.php

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9026
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	15th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2015
Abbreviated title	EvoCOP
Country/Territory	Denmark
City	Copenhagen
Period	8/04/15 → 10/04/15
Internet address	http://www.evostar.org/2015/cfp_evocop.php

Keywords

Cloud computing
Cloud resource management
Genetic algorithm
Optimization
Combinatorial Optimization
Metaheuristics

Access to Document

10.1007/978-3-319-16468-7_1

Cite this

Heilig, L., Lalla-Ruiz, E., & Voß, S. (2015). A biased random-key genetic algorithm for the cloud resource management problem. In G. Ochoa, & F. Chicano (Eds.), Evolutionary Computation in Combinatorial Optimization - 15th European Conference, EvoCOP 2015, Proceedings (pp. 1-12). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9026). Springer. https://doi.org/10.1007/978-3-319-16468-7_1

Heilig, Leonard ; Lalla-Ruiz, Eduardo ; Voß, Stefan. / A biased random-key genetic algorithm for the cloud resource management problem. Evolutionary Computation in Combinatorial Optimization - 15th European Conference, EvoCOP 2015, Proceedings. editor / Gabriela Ochoa ; Francisco Chicano. Springer, 2015. pp. 1-12 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Heilig, L, Lalla-Ruiz, E & Voß, S 2015, A biased random-key genetic algorithm for the cloud resource management problem. in G Ochoa & F Chicano (eds), Evolutionary Computation in Combinatorial Optimization - 15th European Conference, EvoCOP 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9026, Springer, pp. 1-12, 15th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2015, Copenhagen, Denmark, 8/04/15. https://doi.org/10.1007/978-3-319-16468-7_1

A biased random-key genetic algorithm for the cloud resource management problem. / Heilig, Leonard; Lalla-Ruiz, Eduardo; Voß, Stefan.
Evolutionary Computation in Combinatorial Optimization - 15th European Conference, EvoCOP 2015, Proceedings. ed. / Gabriela Ochoa; Francisco Chicano. Springer, 2015. p. 1-12 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9026).

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

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N2 - Flexible use options and associated cost savings of cloud computing are increasingly attracting the interest from both researchers and practitioners. Since cloud providers offer various cloud services in different forms, there is a large potential of optimizing the selection of those services from the consumer perspective. In this paper, we address the Cloud Resource Management Problem that is a recent optimization problem aimed at reducing the payment cost and the execution time of consumer applications. In the related literature, there is one approach that successfully addresses this problem based on a Greedy Randomized Adaptive Search Procedure. Due to the fact that consumers require fast and high-quality solutions to economically automate cloud resource management and deployment processes, we propose an efficient Biased Random-Key Genetic Algorithm. The computational experiments over a benchmark suite generated based on real cloud market offerings indicate that the performance of our approach outperforms the approaches proposed in the literature.

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Heilig L, Lalla-Ruiz E, Voß S. A biased random-key genetic algorithm for the cloud resource management problem. In Ochoa G, Chicano F, editors, Evolutionary Computation in Combinatorial Optimization - 15th European Conference, EvoCOP 2015, Proceedings. Springer. 2015. p. 1-12. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-16468-7_1

A biased random-key genetic algorithm for the cloud resource management problem

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