Abstract-Server consolidation plays a key role to mitigate the continuous power increase of datacenters. The recent advent of scale-out applications (e.g., web search, MapReduce, etc.) necessitate the revisit of existing server consolidation solutions due to distinctively different characteristics compared to traditional high-performance computing (HPC), i.e., user interactive, latency critical, and operations on large data sets split across a number of servers. This paper presents a power saving solution for datacenters that especially targets the distinctive characteristics of the scale-out applications. More specifically, we take into account correlation information of core utilization among virtual machines (VMs) in server consolidation to lower actual peak server utilization. Then, we utilize this reduction to achieve further power savings by aggressively-yet-safely lowering the server operating voltage and frequency level. We have validated the effectiveness of the proposed solution using 1) multiple clusters of real-life scale-out application workloads based web search and 2) utilization traces obtained from real datacenter setups. According to our experiments, the proposed solution provides up to 13.7% power savings with up to 15.6% improvement of Quality-of-Service (QoS) compared to existing correlation-aware VM allocation schemes for datacenters. The soaring demand for computing has produced as collateral undesirable effect a surge in power consumption of servers and datacenters [1] . Server consolidation [3] , which minimizes the number of active servers by packing workloads, or virtual machines (VMs) in a virtualized environment, into the minimal number of active servers, is one of the widely used techniques to reduce the power consumption of datacenters. However, in order to satisfy the performance demand of applications running on servers, server consolidation is usually conducted assuming the worst-case (or peak) utilization [2], [3] . Thus, in order to achieve power consumption without any significant Quality-of-Service (QoS) degradation, many works have presented aggressive consolidation schemes, which pack VMs based on off-peak (e.g., 90th/95th/99th percentile) of server utilization [4], [5] . Recently, correlation of resources utilization patterns among VMs are also exploited, such that, un-correlated VMs are co-located into a server to enable overprovision of VMs under negligible QoS degradation [6]- [9] . Nonetheless, these existing solutions are mostly designed for high-performance computing (HPC) applications and do not
In REF , a power-efficient solution is proposed based on the First-Fit-Decreasing heuristic to separate load correlated VMs especially targeting the characteristics of the scale-out applications.
Correlation-aware virtual machine allocation for energy-efficient datacenters
2013 Design, Automation & Test in Europe Conference & Exhibition (DATE)
2013 Design, Automation & Test in Europe Conference & Exhibition (DATE)
Computer Science