A column generation approach for power-aware optimization of virtualized heterogeneous server clusters

  • Authors:

  • Hugo H. Kramer;Vinicius Petrucci;Anand Subramanian;Eduardo Uchoa

  • Affiliations:

  • Universidade Federal Fluminense, Departamento de Engenharia de Produção, Rua Passo da Pátria, 156 - Bloco E, 4 andar, São Domingos, Niterói-RJ 24210-240, Brazil;Universidade Federal Fluminense, Instituto de Computação, Rua Passo da Pátria, 156 - Bloco E, 3 andar, São Domingos, Niterói-RJ 24210-240, Brazil;Universidade Federal da Paraíba, Departamento de Engenharia de Produção, Centro de Tecnologia, Campus I - Bloco G, Cidade Univesitária, João Pessoa-PB 58051-970, Brazil an ...;Universidade Federal Fluminense, Departamento de Engenharia de Produção, Rua Passo da Pátria, 156 - Bloco E, 4 andar, São Domingos, Niterói-RJ 24210-240, Brazil

  • Venue:
  • Computers and Industrial Engineering
  • Year:
  • 2012

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Abstract

Increasingly, clusters of servers have been deployed in large data centers to support the development and implementation of many kinds of services, having distinct workload demands that vary over time, in a scalable and efficient computing environment. Emerging trends are utility/cloud computing platforms, where many network services, implemented and supported using server virtualization techniques, are hosted on a shared cluster infrastructure of physical servers. The energy consumed to maintain these large server clusters became a very important concern, which in turn, requires major investigation of optimization techniques to improve the energy efficiency of their computing infrastructure. In this work, we propose an efficient approach to solve a relevant cluster optimization problem which, in practice, can be used as an embedded module to implement an integrated power and performance management solution in a real server cluster. The optimization approach simultaneously deals with (i) CPU power-saving techniques combined with server switching on/off mechanisms, (ii) the case of server heterogeneity, (iii) virtualized server environments, (iv) an efficient optimization method, which is based on column generation techniques. The key aspects of our approach are the basis on rigorous and robust optimization techniques, given by high quality solutions in short amount of processing time, and experimental results on the cluster configuration problem for large-scale heterogeneous server clusters that can make use of virtualization techniques.