Differentiated Services with Statistical Real-Time Guarantees in Static-Priority Scheduling Networks

We propose and analyze a methodology for providing absolute differentiated services with statistical performance guarantees for real-time applications in networks that use class-based (as opposed to flow-aware) staticpriority schedulers. We develop a method that can be used to derive statistical delay guarantees in a flow-unaware fashion. Traditionally, both deterministic and statistical delay analysis methods either depend on schedulers that keep per-flow state information, or require detailed information about flow population at delay analysis time. The fact that no such information is needed for delay analysis allows us to perform deadline tests during system (re-)configuration time. We are so able to reduce the runtime admission control to a simple utilization test. No explicit delay computation is necessary at admission time, making this approach scalable to large systems.