Approximation algorithms for bin packing: a survey
Approximation algorithms for NP-hard problems
Ant algorithms for discrete optimization
Artificial Life
Managing energy and server resources in hosting centers
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
pMapper: power and migration cost aware application placement in virtualized systems
Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware
Real time power estimation and thread scheduling via performance counters
ACM SIGARCH Computer Architecture News
Peak power modeling for data center servers with switched-mode power supplies
Proceedings of the 16th ACM/IEEE international symposium on Low power electronics and design
A comparison of high-level full-system power models
HotPower'08 Proceedings of the 2008 conference on Power aware computing and systems
Chaotic attractor prediction for server run-time energy consumption
HotPower'10 Proceedings of the 2010 international conference on Power aware computing and systems
An energy aware framework for virtual machine placement in cloud federated data centres
Proceedings of the 3rd International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet
Costs of Virtual Machine Live Migration: A Survey
SERVICES '12 Proceedings of the 2012 IEEE Eighth World Congress on Services
CHAOS: Composable Highly Accurate OS-based power models
IISWC '12 Proceedings of the 2012 IEEE International Symposium on Workload Characterization (IISWC)
| Hi-index | 0.00 |
The evolution of data centers infrastructures requests clever management systems, as the size of those data-centers can reach several hundreds of physical servers to run each tenths of Virtual Machines. The power consumption of those centers, estimated to 1.3 percent of the world's power consumption in 2011, can be managed using specific policies presented in the literature. One specific data center manager is Entropy, based on the Constraint Programming solver Choco written in Java. We extended Entropy to give it the support of external models, named views. Specifically, we developed a power view, based on generic servers' models, to define and reduce the power consumption of the data center's physical servers. It also relies on generic power models which can handle other resources than memory and CPU. We integrated heuristics and constraints in this view to solve data center reconfiguration problems with power-related constraints and objectives. On the contrary of what is proposed in the literature, this view can be integrated with other models in order to combine their heuristics and user constraints. In this paper, we present the extension we performed in Entropy, the power view we developed, the heuristics and constraints it integrates and we evaluate the power-reduction performances on several reconfiguration problems using our heuristics.