Flexible SLAs in the Cloud with a Partial Utility-Driven Scheduling Architecture

Current clouds SLAs include compensation for customers (i.e. resource renters) with credits when average availability drops below a certain point. However, this credit scheme is too inflexible because consumers lose a non measurable quantity of performance and are only compensated later (i.e. in the next charging cycle). We propose to schedule cloud isolation and execution units, i.e. virtual machines (VMs), driven by the partial utility of applying a certain amount of resources (CPU, memory or bandwidth) to a given VM. This partial utility metric, specified by the customer, allows the provider to transfer resources between VMs. This is particularly relevant for private clouds where resources are not so abundant. We have defined a cost model that incorporates the partial utility the client gives to a certain level of depreciation when VMs are allocated in an over commit environment. CloudSim, a state of the art cloud simulator, was extended to support our partial utility-driven scheduling model. Using simulation scenarios with synthetic and real workloads, we show that our proposed scheduling strategy brings benefits to providers (i.e. revenue, resource utilization) and clients (i.e. workloads' execution time) by incorporating a SLA-based depreciation of computational power, allowing for more VMs to be allocated.