Green Cloud Computing: Challenges and Opportunities
ResumoWe discuss the immediate need, challenges, and opportunities to transition into greener cloud computing platforms. Actions must be taken not only by the academy and the industry, but also by computer science practitioners from several areas, such as information systems, scheduling theory, distributed systems, HPC, computer architecture, and approximate computing, to cite a few.
Cohen, J., Cordeiro, D., and Raphael, P. L. F. (2014). Energy-aware multi-organization scheduling problem. In Euro-Par, pages 186–197. Springer.
Greenpeace (2017). Clicking Green: who is winning the race to build a green Internet. Greenpeace report.
Koot, M. and Wijnhoven, F. (2021). Usage impact on data center electricity needs: A system dynamic forecasting model. Applied Energy, 291:116798.
Lima, J. V. F., Raïs, I., Lefèvre, L., and Gautier, T. (2019). Performance and energy analysis of OpenMP runtime systems with dense linear algebra algorithms. IJHPCA, 33(3):431–443.
Masanet, E., Shehabi, A., Lei, N., Smith, S., and Koomey, J. (2020). Recalibrating global data center energy-use estimates. Science, 367(6481):984–986.
Munhoz, V., Castro, M., and Mendizabal, O. (2022). Strategies for Fault-Tolerant Tightly-coupled HPC Workloads Running on Low-Budget Spot Cloud Infrastructures. In IEEE SBAC-PAD, pages 1–10, Bordeaux. IEEE Computer Society.
Oda, R., Cordeiro, D., and Braghetto, K. R. (2018). Dynamic resource provisioning for scientific workflow executions in clouds. In SCC, pages 291–294. IEEE.
Rocha, F. W., Fukuda, J. C., Francesquini, E., and Cordeiro, D. (2022). Accelerating smart city simulations. In Latin American High Performance Computing Conference, pages 148–162. Springer.
Vasconcelos, M. F. S., Cordeiro, D., and Dufossé, F. (2022). Indirect network impact on the energy consumption in multi-clouds for follow-the-renewables approaches. In 11th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS 2022), pages 44–55. SciTePress.