Klein, CristianHernández-Rodríguez, FranciscoMaggio, MartinaArzen, Karl-ErikGarcía Valls, MarisolCucinotta, Tommaso2013-11-142013-12-122013-12-122013-12-03REACTION 2013, co-located with IEEE RTSS. Vancouver, Canada. December 3rd, 2013. Universidad Carlos III de Madrid, 2013, pp. 37-42.978-84-616-7680-484-616-7680-4https://hdl.handle.net/10016/17919REACTION 2013. 2nd International Workshop on Real-time and distributed computing in emerging applications. December 3rd, 2013, Vancouver, Canada.Resource allocation in clouds is mostly done assuming hard requirements, time-sensitive applications either receive the requested resources or fail, Given the dynamic nature of workloads, guaranteeing on-demand allocations requires large spare capacity. Hence, one cannot have a system that is both reliable and efficient. To mitigate this issue, we introduce service-level awareness in clouds, assuming applications contain some optional code that can be dynamically deactivated as needed. We propose a resource manager that allocates resources to multiple service-level-aware applications in a fair manner. To show the practical applicability, we implemented service-level-aware versions of RUBiS and RUBBoS, two popular cloud benchmarks, together with our resource manager. Experiments show that service-level awareness helps in withstanding flash-crowds or failures, opening up more flexibility in cloud resource management.6application/pdfengAtribución-NoComercial-SinDerivadas 3.0 EspañaSistemas en tiempo realSistemas distribuidosCloud computingResource ManagementReal-timeconference proceedingsTelecomunicacionesopen access3742International Workshop on Real-Time and Distributed Computing in Emerging Applications (REACTION)