FARACost: an adaptation cost model aware of pending constraints

Abstract

The perturbations induced by adaptation and resource allocation decisions on the adapted applications may have the undesirable side effect of causing timing constraint failures. In order to benefit from available adaptation capabilities yet avoid critical timing failures, the dynamic resource allocation mechanism should be aware of the perturbation induced by its decisions. Therefore, the impact of adaptation on short-term performance should be considered a first-class decision criterion, along with traditional criteria such as long-term performance and application criticality. Towards this end, we propose the FARACost, an adaptation cost model that captures the impact of application-specific adaptation procedures and uses this information to evaluate adaptation choices. Experimental evaluations with two applications demonstrate that the use of models like FARA-Cost reduces or prevents pending timing constraint failures, while leading to long-term performance improvements. The experiments are conducted in a cluster environment with a fully implemented infrastructure for adaptation and resource allocation based on the FARA networks.