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               <dc:title>Stay-Away, protecting sensitive applications from performance interference</dc:title>
               <dc:creator>Rameshan, Navaneeth</dc:creator>
               <dc:creator>Navarro Moldes, Leandro</dc:creator>
               <dc:creator>Monte Moreno, Enrique</dc:creator>
               <dc:creator>Vlassov, Vladimir</dc:creator>
               <dc:subject>Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació</dc:subject>
               <dc:subject>Àrees temàtiques de la UPC::Informàtica::Enginyeria del software</dc:subject>
               <dc:subject>Software engineering</dc:subject>
               <dc:subject>Computer software -- Development</dc:subject>
               <dc:subject>Metrics—complexity measures</dc:subject>
               <dc:subject>Performance measures</dc:subject>
               <dc:subject>Performance  interference</dc:subject>
               <dc:subject>Interference  mitigation</dc:subject>
               <dc:subject>Performance sensitivity</dc:subject>
               <dc:subject>Quality of Service</dc:subject>
               <dc:subject>Virtualization</dc:subject>
               <dc:subject>Enginyeria de programari</dc:subject>
               <dc:subject>Programari -- Desenvolupament</dc:subject>
               <dc:description>While co-locating virtual machines improves utilization in&#xd;
resource shared environments, the resulting performance interference&#xd;
between VMs is difficult to model or predict. QoS&#xd;
sensitive applications can suffer from resource co-location&#xd;
with other less short-term resource sensitive or batch applications.&#xd;
The common practice of overprovisioning resources&#xd;
helps to avoid performance interference and guarantee QoS&#xd;
but leads to low machine utilization. Recent work that relies&#xd;
on static approaches suffer from practical limitations due to&#xd;
assumptions such as a priori knowledge of application behaviour&#xd;
and workload.&#xd;
To address these limitations, we present Stay-Away, a&#xd;
generic and adaptive mechanism to mitigate the detrimental&#xd;
effects of performance interference on sensitive applications&#xd;
when co-located with batch applications. Our mechanism&#xd;
complements the allocation decisions of resource schedulers&#xd;
by continuously learning the favourable and unfavourable&#xd;
states of co-execution and mapping them to a state-space&#xd;
representation. Trajectories in this representation are used&#xd;
to predict and prevent any transition towards interference of&#xd;
sensitive applications by proactively throttling the execution&#xd;
of batch applications. The representation also doubles as a&#xd;
template to prevent violations in the future execution of the&#xd;
repeatable sensitive application when co-located with other&#xd;
batch applications. Experimental results with realistic applications&#xd;
show that it is possible to guarantee a high level of&#xd;
QoS for latency sensitive applications while also improving&#xd;
machine utilization.</dc:description>
               <dc:description>Peer Reviewed</dc:description>
               <dc:description>Postprint (published version)</dc:description>
               <dc:date>2014</dc:date>
               <dc:type>Conference report</dc:type>
               <dc:relation>http://doi.acm.org/10.1145/2663165.2663327</dc:relation>
               <dc:rights>http://creativecommons.org/licenses/by-nc-nd/3.0/es/</dc:rights>
               <dc:rights>Restricted access - publisher's policy</dc:rights>
               <dc:rights>Attribution-NonCommercial-NoDerivs 3.0 Spain</dc:rights>
               <dc:publisher>Association for Computing Machinery (ACM)</dc:publisher>
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