ABSTRACT
Our society has become ever more dependent on large datacenters. Search engines, e-commerce and cloud computing are just some of the broadly used services that rely on large scale datacenters. Datacenter managers are reluctant to non-functional changes on the facilities of a perfectly operational installation as failures can be very expensive. Therefore, one of the big challenges of green computing is how to reduce the energy consumption and environmental impact of such systems without compromising the business. In this work, we propose a thermal monitoring tool for datacenters which is based on a WSN composed of ready-to-use modules. This tool provides a better understanding of the thermal behavior of datacenters and can help datacenter managers, for example, to manually adjust the cooling system in order to avoid energy waste and reduce cost. There is very low intrusiveness to the server facilities, as the tool is 100% independent of the server operability and requires only the setup of small wireless and battery powered sensors. Our tool was implemented and tested on a real datacenter in order to demonstrate the feasibility of our approach.
- Comet system. http://www.cometsystem.cz.Google Scholar
- Onset. http://www.onsetcomp.com/.Google Scholar
- F. Ahmad and T. Vijaykumar. Joint optimization of idle and cooling power in data centers while maintaining response time. In ACM Sigplan Notices, pages 243--256, New York, EUA, March 2010. Google ScholarDigital Library
- K. Christensen. Green networks: Opportunities and challenges. In 34th IEEE Conference on Local Computer Networks, page 13, Zurich, Suï¿1/2ï¿1/2a, Outubro 2009.Google ScholarCross Ref
- EPA. Report to congress on server and data center energy efficiency, 2007.Google Scholar
- D. Gay, P. Levis, R. Von Behren, M. Welsh, E. Brewer, and D. Culler. The nesc language: A holistic approach to networked embedded systems. 38(5): 1--11, Maio 2003. Google ScholarDigital Library
- O. Gnawali, R. Fonseca, K. Jamieson, D. Moss, and P. Levis. Collection tree protocol. In 7th ACM Conference on Embedded Networked Sensor Systems, pages 1--14, Novembro 2009. Google ScholarDigital Library
- W. Huang, M. Allen-Ware, J. B. Carter, E. Elnozahy, H. Hamann, T. Keller, C. Lefurgy, J. Li, K. Rajamani, and J. Rubio. Tapo: thermal-aware power optimization techniques for servers and data centers. In 2nd IEEE Green Computing Conference and Workshops, pages 1--8, Orlando, EUA, Julho 2011. Google ScholarDigital Library
- J. Hui. Deluge 2.0 - TinyOs network programming, 2005. http://www.cs.berkeley.edu/jwhui/deluge/delugemanual.pdf.Google Scholar
- J. Koomey. Growth in data center electricity use 2005 to 2010. Analytics Press, 1(1), Agosto 2011.Google Scholar
- P. Levis, S. Madden, J. Polastre, R. Szewczyk, K. Whitehouse, A. Woo, D. Gay, J. Hill, M. Welsh, E. Brewer, et al. TinyOs: an operating system for sensor networks. In Ambient intelligence, pages 115--148. Springer, 2005.Google ScholarCross Ref
- L. Li, C.-J. M. Liang, J. Liu, S. Nath, A. Terzis, and C. Faloutsos. Thermocast: a cyber-physical forecasting model for data centers. In 17th ACM Conference on Knowledge Discovery and Data Mining, volume 11, San Diego, EUA, Agosto 2011. Google ScholarDigital Library
- C.-J. M. Liang, J. Liu, L. Luo, A. Terzis, and F. Zhao. Racnet: a high-fidelity data center sensing network. In 7th ACM Conference on Embedded Networked Sensor Systems, pages 15--28, Novembro 2009. Google ScholarDigital Library
- V. Madan and S. Reddy. Review of wireless sensor mote platforms. 2012.Google Scholar
- J. Mankoff, R. Kravets, and E. Blevis. Some computer science issues in creating a sustainable world. IEEE Computer, 41(8): 102--105, Agosto 2008. Google ScholarDigital Library
- M. Maróti, B. Kusy, G. Simon, and Á. Lédeczi. The flooding time synchronization protocol. In 2nd ACM International Conference on Embedded Networked Sensor Systems, pages 39--49, Baltimore, EUA, Novembro 2004. Google ScholarDigital Library
- M. Maroti and J. Sallai. TEP 133: packet-level time synchronization. Technical report, 2008. http://www.tinyos.net/tinyos-2.1.0/doc/html/tep133.html.Google Scholar
- D. Meisner, B. T. Gold, and T. F. Wenisch. Powernap: eliminating server idle power. In Architectural Support for Programming Languages and Operating Systems, pages 205--216, March 2009. Google ScholarDigital Library
- MEMSIC. Iris datasheet. http://www.memsic.com.Google Scholar
- MEMSIC. MDA 100 datasheet. http://www.memsic.com.Google Scholar
- MEMSIC. MIB 520 datasheet. http://www.memsic.com.Google Scholar
- MEMSIC. Micaz datasheet. http://www.memsic.com.Google Scholar
- D. Moss, J. Hui, and K. Klues. TEP 105: low power listening. 2007. http://www.tinyos.net/tinyos-2.x/doc/html/tep116.html.Google Scholar
- D. Moss and P. Levis. Box-macs: Exploiting physical and link layer boundaries in low-power networking. Technical report, Stanford University, 2008.Google Scholar
- J. Polastre, J. Hill, and D. Culler. Versatile low power media access for wireless sensor networks. In ACM 2nd International Conference on Embedded networked Sensor Systems, pages 95--107, Baltimore, EUA, Novembro 2004. Google ScholarDigital Library
- R. Talaber, T. Brey, and L. Lamers. Using virtualization to improve data center efficiency. Technical report, The Green Grid, 2009.Google Scholar
Index Terms
- Building a WSN infrastructure with COTS components for the thermal monitoring of datacenters
Recommendations
Multi-elastic Datacenters: Auto-scaled Virtual Clusters on Energy-Aware Physical Infrastructures
Computer clusters are widely used platforms to execute different computational workloads. Indeed, the advent of virtualization and Cloud computing has paved the way to deploy virtual elastic clusters on top of Cloud infrastructures, which are typically ...
Load and Thermal-Aware VM Scheduling on the Cloud
Algorithms and Architectures for Parallel ProcessingAbstractVirtualization is one of the key technologies that enable Cloud Computing, a novel computing paradigm aiming at provisioning on-demand computing capacities as services. With the special features of self-service and pay-as-you-use, Cloud Computing ...
Energy Conserving Secure VM Allocation in Untrusted Cloud Computing Environment
Compute '17: Proceedings of the 10th Annual ACM India Compute ConferenceCloud computing is the latest buzz in most of the IT organizations which are witnessing a a trend of migration from traditional computing to cloud computing, thereby reducing their infrastructure cost and improving efficiency and performance. Cloud ...
Comments