Energy-aware load balancing in distributed data centers
Resumo
This paper summarizes the dissertation ”Energy-aware load balancing in distributed data centers”, which proposed two new algorithms for minimizing energy consumption in cloud data centers. Both algorithms consider hierarchical data center network topologies and requests for the allocation of groups of virtual machines (VMs). The Topology-aware Virtual Machine Placement (TAVMP) algorithm deals with the placement of virtual machines in a single data center. It reduces the blocking of requests and yet maintains acceptable levels of energy consumption. The Topology-aware Virtual Machine Selection (TAVMS) algorithm chooses sets of VM groups for migration between different data centers. Its employment leads to relevant overall energy savings.
Referências
Beloglazov, A., Abawajy, J., and Buyya, R. (2012). Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future Generation Computer Systems, 28(5):755 – 768. Special Section: Energy efficiency in large-scale distributed systems.
da Silva, R. A. C. and da Fonseca, N. L. S. (2015a). Algorithm for the placement of groups of virtual machines in data centers. In Communications (ICC), 2015 IEEE International Conference on.
da Silva, R. A. C. and da Fonseca, N. L. S. (2015b). Energy-aware load balancing in distributed data centers. Master’s thesis, Universidade Estadual de Campinas.
da Silva, R. A. C. and da Fonseca, N. L. S. (2015c). Topology-aware virtual machine placement in data centers. Journal of Grid Computing, pages 1–16.
Han, Y., Chan, J., and Leckie, C. (2013). Analysing virtual machine usage in cloud computing. In Services (SERVICES), 2013 IEEE Ninth World Congress on, pages 370–377.
Ilyas, M., Raza, S., Chen, C.-C., Uzmi, Z., and Chuah, C.-N. (2012). Red-bl: Energy solution for loading data centers. In INFOCOM, 2012 Proceedings IEEE, pages 2866–2870.
Koomey, J. (2011). Growth in data center electricity use 2005 to 2010. Oakland, CA: Analytics Press. August.
Mandal, U., Habib, M., Zhang, S., Mukherjee, B., and Tornatore, M. (2013). Greening the cloud using renewable-energy-aware service migration. Network, IEEE, 27(6):36–43.
Meng, X., Pappas, V., and Zhang, L. (2010). Improving the scalability of data center networks with traffic-aware virtual machine placement. In INFOCOM, 2010 Proceedings IEEE, pages 1–9.
da Silva, R. A. C. and da Fonseca, N. L. S. (2015a). Algorithm for the placement of groups of virtual machines in data centers. In Communications (ICC), 2015 IEEE International Conference on.
da Silva, R. A. C. and da Fonseca, N. L. S. (2015b). Energy-aware load balancing in distributed data centers. Master’s thesis, Universidade Estadual de Campinas.
da Silva, R. A. C. and da Fonseca, N. L. S. (2015c). Topology-aware virtual machine placement in data centers. Journal of Grid Computing, pages 1–16.
Han, Y., Chan, J., and Leckie, C. (2013). Analysing virtual machine usage in cloud computing. In Services (SERVICES), 2013 IEEE Ninth World Congress on, pages 370–377.
Ilyas, M., Raza, S., Chen, C.-C., Uzmi, Z., and Chuah, C.-N. (2012). Red-bl: Energy solution for loading data centers. In INFOCOM, 2012 Proceedings IEEE, pages 2866–2870.
Koomey, J. (2011). Growth in data center electricity use 2005 to 2010. Oakland, CA: Analytics Press. August.
Mandal, U., Habib, M., Zhang, S., Mukherjee, B., and Tornatore, M. (2013). Greening the cloud using renewable-energy-aware service migration. Network, IEEE, 27(6):36–43.
Meng, X., Pappas, V., and Zhang, L. (2010). Improving the scalability of data center networks with traffic-aware virtual machine placement. In INFOCOM, 2010 Proceedings IEEE, pages 1–9.
Publicado
04/07/2016
Como Citar
DA SILVA, Rodrigo A. C.; DA FONSECA, Nelson L. S..
Energy-aware load balancing in distributed data centers. In: CONCURSO DE TESES E DISSERTAÇÕES (CTD), 29. , 2016, Porto Alegre.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2016
.
p. 369-374.
ISSN 2763-8820.
DOI: https://doi.org/10.5753/ctd.2016.9133.
