Towards Energy-aware IaaS-PaaS Co-design

Alexandra Carpen-Amarie, Djawida Dib, Anne-Cécile Orgerie, Guillaume Pierre

2014

Abstract

The wide adoption of the cloud computing paradigm plays a crucial role in the ever-increasing demand for energy-efficient data centers. Driven by this requirement, cloud providers resort to a variety of techniques to improve energy usage at each level of the cloud computing stack. However, prior studies mostly consider resource-level energy optimizations in IaaS clouds, overlooking the workload-related information locked at higher levels, such as PaaS clouds. In this position paper, we argue that cross-layer cooperation in clouds is a key to achieving an optimized resource management, both performance and energy-wise. To this end, we claim there is a need for a cooperation API between IaaS and PaaS clouds, enabling each layer to share specific information and to trigger correlated decisions. We identify the drawbacks raised by such co-design objectives and discuss opportunities for energy usage optimizations. Moreover, we outline the design of a set of extension modules for Libcloud to serve as building blocks for cross-layer information sharing and cooperation.

References

  1. Acc (2010). Cloud Computing and Sustainability: The Environmental Benefits of Moving to the Cloud. Technical report, Accenture, Microsoft and WSP Report.
  2. Dib, D., Parlavantzas, N., et al. (2013). Meryn: open, SLAdriven, cloud bursting PaaS. In Proc. of ORMaCloud 7813, pages 1-8, New York, NY, USA. ACM.
  3. Duy, T., Sato, Y., et al. (2010). Performance evaluation of a Green scheduling algorithm for energy savings in cloud computing. In 2010 IEEE Int. Sym. on Par. Dist. Proc., Workshops (IPDPSW), pages 1-8.
  4. Gadafi, A., Tchana, A., et al. (2010). Autonomic energy management in clusters. In Proc. of the 1st ACM Workshop on Green Comp., pages 16-21, NY, USA.
  5. Hlavacs, H., Treutner, T., et al. (2011). Energy consumption side-channel attack at virtual machines in a cloud. In IEEE Int. Conf. on Cloud and Green Comp., pages 605-612.
  6. Jaiantilal, A., Jiang, Y., et al. (2010). Modeling cpu energy consumption for energy efficient scheduling. In Proc. of the 1st Workshop on Green Computing, GCM 7810, pages 10-15, New York, NY, USA. ACM.
  7. Koomey, J. (2011). Growth in data center electricity use 2005 to 2010. Oakland, CA: Analytics Press, 1.
  8. Libcloud (2014). Apache Libcloud. http://libcloud.apache.org/.
  9. Liu, H., Xu, C.-Z., et al. (2011). Performance and energy modeling for live migration of virtual machines. In Proc. of the 20th ACM Int. Sym. on High Performance Dist. Comp. (HPDC 7811), pages 171-182, USA.
  10. Meisner, D., Gold, B. T., and Wenisch, T. F. (2009). Powernap: eliminating server idle power. SIGPLAN Notices, 44(3):205-216.
  11. Orgerie, A.-C., Lefevre, L., and Gelas, J.-P. (2010). Demystifying energy consumption in grids and clouds. In Proc. of the Int. Green Comp. Conf., pages 335-342.
  12. Phan, D. H., Suzuki, J., et al. (2012). Evolutionary multiobjective optimization for green clouds. In Proc. of the 14th ACM Int. Conf. on Genetic and Evolutionary Computation Conf. Companion, GECCO Companion 7812, pages 19-26, New York, NY, USA.
  13. Pierre, G. and Stratan, C. (2012). ConPaaS: a platform for hosting elastic cloud applications. IEEE Internet Computing, 16(5):88-92.
  14. Singh, R. P., Keshav, S., et al. (2013). A cloud-based consumer-centric architecture for energy data analytics. In Proc. of the 4th ACM Int. Conf. on Future energy systems, e-Energy 7813, pages 63-74, USA.
  15. Takouna, I., Dawoud, W., et al. (2011). Dynamic configuration of virtual machine for power-proportional resource provisioning. In Proc. of the ACM Int. Workshop on Green Comp. Middleware, pages 1-6, USA.
  16. Zhang, Q., Hellerstein, J., et al. (2011). Characterizing Task Usage Shapes in Google's Compute Clusters. In Int. Workshop on Large Scale Distributed Systems and Middleware.
Download


Paper Citation


in Harvard Style

Carpen-Amarie A., Dib D., Orgerie A. and Pierre G. (2014). Towards Energy-aware IaaS-PaaS Co-design . In Proceedings of the 3rd International Conference on Smart Grids and Green IT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-025-3, pages 203-208. DOI: 10.5220/0004961402030208


in Bibtex Style

@conference{smartgreens14,
author={Alexandra Carpen-Amarie and Djawida Dib and Anne-Cécile Orgerie and Guillaume Pierre},
title={Towards Energy-aware IaaS-PaaS Co-design},
booktitle={Proceedings of the 3rd International Conference on Smart Grids and Green IT Systems - Volume 1: SMARTGREENS,},
year={2014},
pages={203-208},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004961402030208},
isbn={978-989-758-025-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Smart Grids and Green IT Systems - Volume 1: SMARTGREENS,
TI - Towards Energy-aware IaaS-PaaS Co-design
SN - 978-989-758-025-3
AU - Carpen-Amarie A.
AU - Dib D.
AU - Orgerie A.
AU - Pierre G.
PY - 2014
SP - 203
EP - 208
DO - 10.5220/0004961402030208