Scheduling approaches for green cloud computing: a survey
Abstract
The popularization of Cloud Computing platforms resulted in a significant increase in the use of electricity for platform operations: about 1% of the world's energy consumption is now due to data centers. This paper presents an exploratory review on the computational resources management techniques and scheduling algorithms for cloud computing platforms aiming to maximize the use of renewable energy.
Keywords:
Scheduling, cloud computing, green computing, renewable energy
References
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Camus, B., Dufossé, F., and Orgerie, A.-C. (2017). A stochastic approach for optimizing green energy consumption in distributed clouds. In SMARTGREENS 2017 - International Conference on Smart Cities and Green ICT Systems, Porto, Portugal.
Camus, B., Dufossé, F., Blavette, A., Quinson, M., and Orgerie, A. (2018b). Network-Aware Energy-Efficient Virtual Machine Management in Distributed Cloud Infrastructures with On-Site Photovoltaic Production. In 2018 30th International Symposium on Computer Architecture and High Performance Computing, pages 86–92, Lyon, France.
De Courchelle, I., Guérout, T., Da Costa, G., Monteil, T., and Labit, Y. (2019). Green energy efficient scheduling management. Simulation Modelling Practice and Theory, 93:208–232.
Deng, W., Liu, F., Jin, H., Li, B., and Li, D. (2014). Harnessing renewable energy in cloud datacenters: opportunities and challenges. IEEE Network, 28(1):48–55.
Greenpeace (2017). "Clicking Clean - Greenpeace International", [link], Janeiro.
Gu, C., Huang, H., and Jia, X. (2016). Green scheduling for cloud data centers using esds to store renewable energy. In 2016 IEEE International Conference on Communications (ICC), pages 1–7, Kuala Lumpur, Malasia. IEEE.
IEA (2019). "Data centres and data transmission networks", [link], June.
Lei, H., Zhang, T., Liu, Y., Zha, Y., and Zhu, X. (2015). Sgeess: Smart green energy-efficient scheduling strategy with dynamic electricity price for data center. Journal of Systems and Software, 108:23–38.
Li, Y., Orgerie, A., and Menaud, J. (2015). Opportunistic Scheduling in Clouds Partially Powered by Green Energy. In 2015 IEEE International Conference on Data Science and Data Intensive Systems, pages 448–455, Sydney, NSW, Australia. IEEE.
Li, Y., Orgerie, A., and Menaud, J. (2017). Balancing the use of batteries and opportunistic scheduling policies for maximizing renewable energy consumption in a cloud datacenter. In 2017 25th Euromicro International Conference on Parallel, Distributed andNetwork-based Processing (PDP), pages 408–415, São Petersburgo, Russia. IEEE.
Pierson, J., Baudic, G., Caux, S., Celik, B., Costa, G. D., Grange, L., Haddad, M., Lecui-vre, J., Nicod, J., Philippe, L., Rehn-Sonigo, V., Roche, R., Rostirolla, G., Sayah, A.,Stolf, P., Thi, M., and Varnier, C. (2019). Datazero: Datacenter with zero emission and robust management using renewable energy. IEEE Access, 7:103209–103230.
SIMA (2019). SIMA divulga balanço energético do estado de SP 2019, [link], Setembro.
Published
2020-08-19
How to Cite
VASCONCELOS, Miguel F. S.; CORDEIRO, Daniel.
Scheduling approaches for green cloud computing: a survey. In: REGIONAL SCHOOL OF HIGH PERFORMANCE COMPUTING FROM SÃO PAULO (ERAD-SP), 11. , 2020, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 110-113.
DOI: https://doi.org/10.5753/eradsp.2020.16899.
