Management in Instrumented Datacenters

Abstract —Virtual Machine (VM) migration is one of the mostcommon techniques used to alleviate thermal anomalies (i.e.,hotspots) in cloud datacenter’s servers of by reducing the loadand, therefore, decreasing the server utilization. However, thereare other techniques such as voltage scaling that also can beapplied to reduce the temperature of the servers in datacenters.Because no single technique is the most efficient to meet temper-ature/performance optimization goals in all situations, weworktowards an autonomic approach that performs energy-efficientthermal management while ensuring the Quality of Service (QoS)delivered to the users.In this paper, we explore ways to take actions to reduceenergy consumption at the server side before performing costlymigrations of VMs. Specifically, we focus on exploiting VMMonitor (VMM) configurations, such as pinning techniques inXen platforms, which are complementary to other techniques atthe physical server layer such as using low power modes. Tosupport the arguments of our approach, we present the resultsobtained from an experimental evaluation on real hardware usingHigh Performance Computing (HPC) workloads on differentscenarios.

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