Scheduling of Cloud Computing Tasks via Intelligent Optimization Methods

Ahmed Chiheb Ammari; Wael Labidi; Manar Aldaoud; Faisal Mnif; Haitao Yuan; Meng Chu Zhou; Mohammed Sarrab

doi:10.1007/978-981-19-2397-5_21

Scheduling of Cloud Computing Tasks via Intelligent Optimization Methods

Ahmed Chiheb Ammari, Wael Labidi, Manar Aldaoud, Faisal Mnif, Haitao Yuan, Meng Chu Zhou, Mohammed Sarrab

Electrical and Computer Engineering

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

Abstract

Distributed green cloud datacenters (DGCDs) are increasingly deployed around the world. DGCDs integrate many renewable sources to provide clean power and decrease their operating cost. They are spread over multiple locations, where renewable energy availability, bandwidth prices and grid electricity costs have high geographical diversity. This paper focuses on delay-bounded applications in DGCDs and performs cost and energy-effective scheduling of multiple heterogeneous applications subject to delay-bound constraints. The minimization problem of operational cost of DGCDs is formulated and successfully solved by using Firefly, bat, and simulated annealing-bat algorithms. Data-driven experiments are conducted to assess and compare their effectiveness to solve it. The Firefly algorithm is shown to well outperform its peers.

Original language	English (US)
Title of host publication	Proceedings of 7th International Congress on Information and Communication Technology - ICICT 2022
Editors	Xin-She Yang, Simon Sherratt, Nilanjan Dey, Amit Joshi
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	209-221
Number of pages	13
ISBN (Print)	9789811923968
DOIs	https://doi.org/10.1007/978-981-19-2397-5_21
State	Published - 2023
Event	7th International Congress on Information and Communication Technology, ICICT 2022 - Virtual, Online Duration: Feb 21 2022 → Feb 24 2022

Publication series

Name	Lecture Notes in Networks and Systems
Volume	465
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	7th International Congress on Information and Communication Technology, ICICT 2022
City	Virtual, Online
Period	2/21/22 → 2/24/22

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Signal Processing
Computer Networks and Communications

Keywords

Bat algorithm
Cloud computing
Cost optimization
Firefly algorithm
Simulated annealing
Task scheduling

Access to Document

10.1007/978-981-19-2397-5_21

Cite this

Ammari, A. C., Labidi, W., Aldaoud, M., Mnif, F., Yuan, H., Zhou, M. C., & Sarrab, M. (2023). Scheduling of Cloud Computing Tasks via Intelligent Optimization Methods. In X.-S. Yang, S. Sherratt, N. Dey, & A. Joshi (Eds.), Proceedings of 7th International Congress on Information and Communication Technology - ICICT 2022 (pp. 209-221). (Lecture Notes in Networks and Systems; Vol. 465). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-2397-5_21

Ammari, Ahmed Chiheb ; Labidi, Wael ; Aldaoud, Manar et al. / Scheduling of Cloud Computing Tasks via Intelligent Optimization Methods. Proceedings of 7th International Congress on Information and Communication Technology - ICICT 2022. editor / Xin-She Yang ; Simon Sherratt ; Nilanjan Dey ; Amit Joshi. Springer Science and Business Media Deutschland GmbH, 2023. pp. 209-221 (Lecture Notes in Networks and Systems).

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title = "Scheduling of Cloud Computing Tasks via Intelligent Optimization Methods",

abstract = "Distributed green cloud datacenters (DGCDs) are increasingly deployed around the world. DGCDs integrate many renewable sources to provide clean power and decrease their operating cost. They are spread over multiple locations, where renewable energy availability, bandwidth prices and grid electricity costs have high geographical diversity. This paper focuses on delay-bounded applications in DGCDs and performs cost and energy-effective scheduling of multiple heterogeneous applications subject to delay-bound constraints. The minimization problem of operational cost of DGCDs is formulated and successfully solved by using Firefly, bat, and simulated annealing-bat algorithms. Data-driven experiments are conducted to assess and compare their effectiveness to solve it. The Firefly algorithm is shown to well outperform its peers.",

keywords = "Bat algorithm, Cloud computing, Cost optimization, Firefly algorithm, Simulated annealing, Task scheduling",

author = "Ammari, {Ahmed Chiheb} and Wael Labidi and Manar Aldaoud and Faisal Mnif and Haitao Yuan and Zhou, {Meng Chu} and Mohammed Sarrab",

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language = "English (US)",

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Ammari, AC, Labidi, W, Aldaoud, M, Mnif, F, Yuan, H, Zhou, MC & Sarrab, M 2023, Scheduling of Cloud Computing Tasks via Intelligent Optimization Methods. in X-S Yang, S Sherratt, N Dey & A Joshi (eds), Proceedings of 7th International Congress on Information and Communication Technology - ICICT 2022. Lecture Notes in Networks and Systems, vol. 465, Springer Science and Business Media Deutschland GmbH, pp. 209-221, 7th International Congress on Information and Communication Technology, ICICT 2022, Virtual, Online, 2/21/22. https://doi.org/10.1007/978-981-19-2397-5_21

Scheduling of Cloud Computing Tasks via Intelligent Optimization Methods. / Ammari, Ahmed Chiheb; Labidi, Wael; Aldaoud, Manar et al.
Proceedings of 7th International Congress on Information and Communication Technology - ICICT 2022. ed. / Xin-She Yang; Simon Sherratt; Nilanjan Dey; Amit Joshi. Springer Science and Business Media Deutschland GmbH, 2023. p. 209-221 (Lecture Notes in Networks and Systems; Vol. 465).

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

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T1 - Scheduling of Cloud Computing Tasks via Intelligent Optimization Methods

AU - Ammari, Ahmed Chiheb

AU - Labidi, Wael

AU - Aldaoud, Manar

AU - Mnif, Faisal

AU - Yuan, Haitao

AU - Zhou, Meng Chu

AU - Sarrab, Mohammed

PY - 2023

Y1 - 2023

N2 - Distributed green cloud datacenters (DGCDs) are increasingly deployed around the world. DGCDs integrate many renewable sources to provide clean power and decrease their operating cost. They are spread over multiple locations, where renewable energy availability, bandwidth prices and grid electricity costs have high geographical diversity. This paper focuses on delay-bounded applications in DGCDs and performs cost and energy-effective scheduling of multiple heterogeneous applications subject to delay-bound constraints. The minimization problem of operational cost of DGCDs is formulated and successfully solved by using Firefly, bat, and simulated annealing-bat algorithms. Data-driven experiments are conducted to assess and compare their effectiveness to solve it. The Firefly algorithm is shown to well outperform its peers.

AB - Distributed green cloud datacenters (DGCDs) are increasingly deployed around the world. DGCDs integrate many renewable sources to provide clean power and decrease their operating cost. They are spread over multiple locations, where renewable energy availability, bandwidth prices and grid electricity costs have high geographical diversity. This paper focuses on delay-bounded applications in DGCDs and performs cost and energy-effective scheduling of multiple heterogeneous applications subject to delay-bound constraints. The minimization problem of operational cost of DGCDs is formulated and successfully solved by using Firefly, bat, and simulated annealing-bat algorithms. Data-driven experiments are conducted to assess and compare their effectiveness to solve it. The Firefly algorithm is shown to well outperform its peers.

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Y2 - 21 February 2022 through 24 February 2022

ER -

Ammari AC, Labidi W, Aldaoud M, Mnif F, Yuan H, Zhou MC et al. Scheduling of Cloud Computing Tasks via Intelligent Optimization Methods. In Yang XS, Sherratt S, Dey N, Joshi A, editors, Proceedings of 7th International Congress on Information and Communication Technology - ICICT 2022. Springer Science and Business Media Deutschland GmbH. 2023. p. 209-221. (Lecture Notes in Networks and Systems). doi: 10.1007/978-981-19-2397-5_21

Scheduling of Cloud Computing Tasks via Intelligent Optimization Methods

Abstract

Publication series

Conference

All Science Journal Classification (ASJC) codes

Keywords

Access to Document

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