Networking-computing resource allocation for hard real-time Green Cloud applications

Performing real-time applications on top of virtualized cloud systems requires that the overall per-job delay due to the in-cloud processing is upper bounded in a hard way. This opens the question about the optimal dynamic joint allocation of both computing and networking resources hosted in the Cloud. This is the focus of this contribution, where we develop in closed-form the optimal fully scalable energy-saving scheduler for the joint allocation of the task sizes, communication rates and processing rates in delay-constrained Clouds composed by multiple frequency-scalable parallel Virtual Machines (VMs).