• DocumentCode
    3577312
  • Title

    Coordinating VMs´ Memory Demand Heterogeneity and Memory DVFS for Energy-Efficient VMs Consolidation

  • Author

    Takouna, Ibrahim ; Meinel, Christoph

  • Author_Institution
    Hasso Plattner Inst., Univ. of Potsdam, Potsdam, Germany
  • fYear
    2014
  • Firstpage
    478
  • Lastpage
    485
  • Abstract
    We propose memory-aware VM consolidation to achieve energy-efficiency of a data center while enhancing performance of VMs. Consolidation without awareness of the memory-access demand can cause inefficient resource utilization and degrade system performance. In this chapter, we propose efficient consolidation of VMs based on the memory-access demand of these VMs to improve overall system performance. The proposed algorithm, Memory-bus Load Balancing (MLB), is executed by the Global Migration Manger (GMM). We evaluated our algorithm using several simulation setups and several performance metrics, such as performance degradation, VM placement, memory-bus utilization of each server, and energy consumption. The results showed that we could achieve balance in memory-bus utilization of servers and improve performance of the system compared to the CPU-based consolidation approach. Furthermore, we investigated the effectiveness of using the memory DVFS mechanism to achieve efficient energy consumption.
  • Keywords
    energy consumption; power aware computing; storage management; virtual machines; VM memory demand heterogeneity; VM placement; energy consumption; energy-efficiency; global migration manger; memory DVFS; memory-access demand; memory-aware VM consolidation; memory-bus load balancing; Bandwidth; Benchmark testing; Degradation; Energy consumption; Memory management; Runtime; Servers; consolidation; management; memory-bus; power; virtualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Internet of Things (iThings), 2014 IEEE International Conference on, and Green Computing and Communications (GreenCom), IEEE and Cyber, Physical and Social Computing(CPSCom), IEEE
  • Print_ISBN
    978-1-4799-5967-9
  • Type

    conf

  • DOI
    10.1109/iThings.2014.85
  • Filename
    7059711