ew 15(6): e4

Research Article

Multi-Class Queuing Networks Models for Energy Optimization

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  • @ARTICLE{10.4108/icst.valuetools.2014.258214,
        author={Davide Cerotti and Marco Gribaudo and Pietro Piazzolla and Riccardo Pinciroli and Giuseppe Serazzi},
        title={Multi-Class Queuing Networks Models for Energy Optimization},
        journal={EAI Endorsed Transactions on Energy Web},
        volume={2},
        number={6},
        publisher={EAI},
        journal_a={EW},
        year={2015},
        month={2},
        keywords={performance, energy optimization, energy-aware scheduling, queuing network, multi-class workload, load control policies},
        doi={10.4108/icst.valuetools.2014.258214}
    }
    
  • Davide Cerotti
    Marco Gribaudo
    Pietro Piazzolla
    Riccardo Pinciroli
    Giuseppe Serazzi
    Year: 2015
    Multi-Class Queuing Networks Models for Energy Optimization
    EW
    EAI
    DOI: 10.4108/icst.valuetools.2014.258214
Davide Cerotti1,*, Marco Gribaudo1, Pietro Piazzolla1, Riccardo Pinciroli1, Giuseppe Serazzi1
  • 1: Politecnico di Milano
*Contact email: davide.cerotti@polimi.it

Abstract

The increase of energy consumption and the related costs in large data centers has stimulated new researches on techniques to optimize the power consumption of the servers. In this paper we focus on systems that should process a peak workload consisting of different classes of applications. The objective is to implement a policy of load control which allows an efficient use of the power deployed to the resources. The proposed strategy controls the workload mix in order to achieve the maximum utilization of all the resources allocated. As a consequence, the power provision will be fully utilized and the throughput maximized. Thus, the costs to execute a given workload will be minimized, together with its energy consumption, since the required processing time is decreased.