Adaptive Co-Allocation of Distributed Resources for Parallel Applications

Parallel applications can speed up their execution by accessing resources hosted by multiple autonomous providers. Applications following the message passing model de-mand processors to be available at the same time; a problem known as resource co-allocation. Other application models, such as workflows and bag-of-tasks (BoT), can also benefit from the coordinated allocation of resources from autonomous providers. Ap-plications waiting for resources require constant rescheduling. However, different from single-provider settings, rescheduling across multiple providers is challenging due to the autonomy and information availability participants are willing to disclose. This thesis contributes to the area of distributed systems by proposing adaptive re-source co-allocation policies for message passing and BoT applications, which aim at reducing user response time and increasing system utilisation. For message passing appli-cations, the co-allocation policies rely on start time shifting and process remapping opera-tions, whereas for BoT applications, the policies consider limited information access from providers and coordinated rescheduling. This thesis also shows practical deployment o