Abstract—Desirable application performance is typically guaranteed through the use of Service Level Agreements (SLAs) that specify fixed fractions of resource capacities that must be allocated for unencumbered use by the application. The mapping between what constitutes desirable performance and SLAs is not unique: multiple SLA expressions might be functionally equivalent. Having the flexibility to transform SLAs from one form to another in a manner that is provably safe would enable hosting solutions to achieve significant efficiencies. This paper demonstrates the promise of such an approach by proposing a type-theoretic framework for the representation and safe transformation of SLAs. Based on that framework, the paper describes a methodical approach for the inference of efficient and safe mappings of periodic, real-time tasks to the physical and virtual hosts that constitute a hierarchical scheduler. Extensive experimental results support the conclusion that the flexibility afforded by safe SLA transformations has the potential to yield significant savings. I.

Abstract—In hosting environments such as IaaS clouds, desirable application performance is usually guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated for unencumbered use for proper operation. Arbitrary colocation of applications with different SLAs on a single host may result in inefficient utilization of the host’s resources. In this paper, we propose that periodic resource allocation and consumption models – often used to characterize real-time workloads – be used for a more granular expression of SLAs. Our proposed SLA model has the salient feature that it exposes flexibilities that enable the infrastructure provider to safely transform SLAs from one form to another for the purpose of achieving more efficient colocation. Towards that goal, we present MORPHOSYS: a framework for a service that allows the manipulation of SLAs to enable efficient colocation of arbitrary workloads in a dynamic setting. We present results from extensive trace-driven simulations of colocated Video-on-Demand servers in a cloud setting. These results show that potentially-significant reduction in wasted resources (by as much as 60%) are possible using MORPHOSYS. I.

An increased number of applications, such as computational grids, testbeds, peer-to-peer networks, and sensor networks (among many others) rely on finding a set of resources that meet certain criteria for their operation. In particular, in