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vGreen : A System for Energy Efficient Manager in Virtualized Environments

vGreen : A System for Energy Efficient Manager in Virtualized Environments. G. Dhiman , G Marchetti , T Rosing ISLPED 2009. vGreen. Multi-tiered software system for energy efficient computing and management in virtualized environments.

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vGreen : A System for Energy Efficient Manager in Virtualized Environments

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  1. vGreen: A System for Energy Efficient Managerin Virtualized Environments G. Dhiman, G Marchetti, T Rosing ISLPED 2009

  2. vGreen • Multi-tiered software system for energy efficient computing and management in virtualized environments. • Captures power and performance characteristics of virtual machines and develops policies for energy efficient VM scheduling. • Performance and system level energy savings of 20% and 15%

  3. Importance • Power Consumption critical • because it impacts deployment (peak power delivery) • Affects operational costs (power supply, cooling) • Current work treats overall CPU utilization of PM and its VM as indicator for power consumption and resource utilization • Characteristics of co located VMs causes variation in power consumption at similar CPU utilization levels.

  4. Solution technique • vGreen • Understand and exploit relationship between architectural characteristics of VM and its performance and power consumption. • Architectural characteristics comprise of instructions per cycle, memory access • Based on client server model • Vgserv and vgnodes

  5. vgserv and vgnodes • Vgserv • Centralized server • Performs management decisions like scheduling and DVFS of VMs across PMs • Places VMs across vgnodes to improve overall performance • Vgnodes • Physical Machines where VMs located • Perform online characterization of the VMs running on them and updates vgserv

  6. Principle and methodology • Nature of workload executed in each VM determines the power profile and performance of the VM, and thereby its energy consumption. • VMs with different or same characteristics co-located in same VM • Characteristics refer to CPU and memory utilization • Two contrasting benchmarks mcf and perl used to implement heterogeneous characteristics

  7. eonand mcf • mcf • High Memory Accesses per cycle (MPC) • Results in increased cache conflict rate for multiple instances • Increased execution time • eon • Has high Instructions per cycle but low MPC • Results in higher utilization of CPU resource

  8. Comparison of mcf and eon

  9. Conclusion from results • Co-scheduling VMs with similar characteristics not beneficial from energy efficiency and power consumption point of view. • mcf contributes to higher system energy consumption because of its longer running time. • eoncontributes to power imbalance as it consumes more power • Running VMs with mcf and eonon both PMs result in high performance improvement and energy savings upto 20%

  10. Power Management in Virtualized

  11. Hierarchical Metrics

  12. Explanation • vgpolicy decisions based on value of different metrics, namely MPC, IPC and utilization of different VMs • These metrics received as updates from vgnodes. • Metrics evaluated and updated dynamically

  13. Continued… • vgxen estimates aggregate metrics (vMPC, vIPC, vutil) for each VM by adding up metrics of constituent VCPU and stores it and exports it to vgpolicy through vgdom vgnode. • vgdom acts as interface for vgnode to vgserv and registers vgnode with vgserv.

  14. MPC balance algorithm

  15. Explanation • Checks if nMPC of n1 greater than threshold MPC. • Return if small otherwise find VM with minimum vMPC in n1 and migrate it to vgnode with lower nMPC for better balance. • But migration should not result in the nMPC of new node exceeding threshold MPC. • Same procedure for IPC. • Utilization is balanced to ensure no overcommitted or underutilized node exists. • VM consolidation of low utilization VM to idle VM

  16. DVFS • Vgpolicy issues command to scale v-f setting if it is more energy efficient than VM migration. • Can be required if heterogeneous VMs are absent. • Exploit characteristics of workload to find v-f setting that is best suited. • mcf and eon run at 90% CPU utilization levels

  17. Different frequency levels

  18. MPC, IPC, DVFS • MPC highest priority • Memory bottleneck impacts performance and energy efficiency • IPC next • Balanced power consumption, results in uniform thermal profile and decreases cooling cost. • Utilization for fair distribution of workload. • DVFS when no benefits obtained from VM scheduling

  19. Average Weighted Speedup • Average Weighted speedup • Te+i = time of execution of VMi with E+ • Tvgreeni = time of execution of VMi with vGreen • Talonei = time of execution of VMi running alone on VMi

  20. Mixed vs Same VM placement

  21. Weighted Speedup and Energy Savings

  22. Power Consumption

  23. Conclusion • vGreen has negligible runtime overhead • Workload characterization achieves better performance and energy efficiency • Reduces power consumption variance between two vgnodes by 80%

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