Energy proportional and opportunistic computing systems

Our first goal is to design an energy-proportional-computing system (EPCS), which implies no energy consumption, whenever there is no activity. To date, dynamic power management has been widely used in embedded systems as an effective energy saving method with a policy that attempts to adjust the power mode according to the workload variations. Unfortunately, servers consume energy even when they are idle. For an efficient EPCS, we need to have the capability to turn on/off servers dynamically. Vary-on/vary-off (VOVO) policy reduces the aggregate-power consumption of a server cluster during periods of reduced workload. The VOVO policy turns off servers so that only the minimum number of servers that can support the workload are kept alive. 

However, much of the applications running in a data center must be online constantly. To solve this problem, dynamic placement using application live migration permits to keep using VOVO policy in the on-line application context. Live migration moves a running application between different physical ma- chines without disconnecting the client or application. Memory, storage, and network connectivity are trans- ferred from the original host machine to the desti- nation. Currently, the most efficient system for live migration is the use of virtualization. Virtualization refers to the creation of a virtual machine (VM) that acts like a real computer with an operating system but software executed on these VMs is separated from the underlying hardware resources. Virtualization also al- lows snapshots, fail-over and globally reduce the IT energy consumption by consolidating VMs on a physical machine (i.e. increasing the server utilization and thus reducing the energy footprint). Furthermore, dynamic consolidation uses live migration for effective placement of VMs on the pool of DC servers to re- duce energy, increase security, etc. But live migration requires significant network resources. 

Our first main objective is more concentrated on Workload-driven approach. EpoCloud adapts the power consumption of the DC depending on the application workload. Our second objective is more focused on Power-driven SLA. The Power-driven approach implies shifting or scheduling the postponable workloads to the time period when the electricity is available (from the renewable energy sources) or at the best price. For on-line application, power-driven approach implies a degradation of services when energy is at a insufficient level, while maintaining SLAs. In addition, EpoCloud takes advantage of the available energy to perform some tasks. Some of them allow limitations on application degradation. 

  1. EpoCloud architecture  
  2. EpoCloud manager