Diego Perez-Palacin
José Merseguer
ABSTRACT
The energy use is becoming a key design consideration in computing infrastructures and services. In this paper we focus on service-based applications and we propose an adaptation process that can be used to reduce power consumption. This adaptation process is materialized in an adaptation plan which fits into a software architecture specifically designed for self-adaptive systems. The adaptation plan guarantees a trade-off between energy consumption and QoS offered, while maintaining suitable revenues for the service provider. The proposed approach is based on the principle of proportional energy consumption obtained by scaling down energy for unused resources, considering both the number of servers switched on and the operating frequencies of that servers.
- L. Bertini, J. C. Leite, and D. Mossè. Power optimization for dynamic configuration in heterogeneous web server clusters. Journal of Systems and Software, 83(4):585--598, 2010. Google Scholar
Digital Library
- R. Bianchini and R. Rajamony. Power and energy management for server systems. Computer, 37(11):68--76, 2004. Google ScholarDigital Library
- J. Chase and R. Doyle. Balance of power: Energy management for server clusters. In HotOS'01, May 2001. Google ScholarDigital Library
- Y. Chen, A. Das, W. Qin, A. Sivasubramaniam, Q. Wang, and N. Gautam. Managing server energy and operational costs in hosting centers. SIGMETRICS Perform. Eval. Rev., 33(1):303--314, 2005. Google ScholarDigital Library
- B. H. C. Cheng, R. de Lemos, H. Giese, P. Inverardi, and J. Magee, editors. Software Engineering for Self-Adaptive Systems {outcome of a Dagstuhl Seminar}, volume 5525 of Lecture Notes in Computer Science. Springer, 2009. Google ScholarDigital Library
- E. N. Elnozahy, M. Kistler, and R. Rajamony. Energy-efficient server clusters. PACS'02, pages 179--197, Berlin, Heidelberg, 2003. Springer-Verlag. Google ScholarDigital Library
- J. O. Kephart and D. M. Chess. The vision of autonomic computing. IEEE Computer, 36(1):41--50, 2003. Google ScholarDigital Library
- J. Kramer and J. Magee. Self-managed systems: an architectural challenge. In FOSE '07: 2007 Future of Software Engineering, pages 259--268, Washington, DC, USA, 2007. IEEE Computer Society. Google ScholarDigital Library
- J. López-Grao, J. Merseguer, and J. Campos. From UML activity diagrams to stochastic Petri nets: Application to software performance engineering. In Proceedings of WOSP'04, pages 25--36, Redwood City, California, USA, January 2004. ACM. Google ScholarDigital Library
- Object Management Group, http://www.promarte.org. A UML Profile for MARTE., 2005.Google Scholar
- D. Perez-Palacin and J. Merseguer. Performance sensitive self-adaptive service-oriented software using hidden markov models. In Proceedings of WOSP/SIPEW '11, pages 201--206, 2011. Google ScholarDigital Library
- D. Perez-Palacin, J. Merseguer, and S. Bernardi. Performance aware open-world software in a 3-layer architecture. In WOSP/SIPEW '10, pages 49--56, New York, NY, USA, 2010. ACM. Google ScholarDigital Library
- P. Ranganathan. Recipe for efficiency: principles of power-aware computing. Commun. ACM, 53:60--67, April 2010. Google ScholarDigital Library
Index Terms
- Enhancing a QoS-based self-adaptive framework with energy management capabilities
Recommendations
QoS and energy management with Petri nets: A self-adaptive framework
Energy use is becoming a key design consideration in computing infrastructures and services. In this paper we focus on service-based applications and we propose an adaptation framework that can be used to reduce power consumption according to the ...
Energy consumption modeling for hybrid computing
Euro-Par'12: Proceedings of the 18th international conference on Parallel ProcessingEnergy efficiency is increasingly critical for embedded systems and mobile devices, where their continuous operation is based on battery life. In order to increase energy efficiency, chip manufacturers are developing heterogeneous CMP chips.
We present ...
Towards optimizing energy costs of algorithms for shared memory architectures
SPAA '10: Proceedings of the twenty-second annual ACM symposium on Parallelism in algorithms and architecturesEnergy consumption by computer systems has emerged as an important concern. However, the energy consumed in executing an algorithm cannot be inferred from its performance alone: it must be modeled explicitly. This paper analyzes energy consumption of ...
Comments