Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Power provisioning for a warehouse-sized computer
Proceedings of the 34th annual international symposium on Computer architecture
PowerNap: eliminating server idle power
Proceedings of the 14th international conference on Architectural support for programming languages and operating systems
Shares and utilities based power consolidation in virtualized server environments
IM'09 Proceedings of the 11th IFIP/IEEE international conference on Symposium on Integrated Network Management
Energy aware consolidation for cloud computing
HotPower'08 Proceedings of the 2008 conference on Power aware computing and systems
Evolutionary Optimal Virtual Machine Placement and Demand Forecaster for Cloud Computing
AINA '11 Proceedings of the 2011 IEEE International Conference on Advanced Information Networking and Applications
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Increasing power consumption of IT infrastructures and growing electricity prices have led to the development of several energy-saving techniques in the last couple of years. Virtualization and consolidation of services is one of the key technologies in data centers to reduce overprovisioning and therefore increase energy savings. This paper shows that the energy-optimal allocation of virtualized services in a heterogeneous server infrastructure is NP-hard and can be modeled as a variant of the multidimensional vector packing problem. Furthermore, it proposes a model to predict the performance degradation of a service when it is consolidated with other services. The model allows considering the tradeoff between power consumption and service performance during service allocation. Finally, the paper presents two heuristics that approximate the energy-optimal and performance-aware resource allocation problem and shows that the allocations determined by the proposed heuristics are more energy-efficient than the widely applied maximum-density consolidation.