Statistical admission control for real-time services under earliest deadline first scheduling
The design of call admission control (CAC) mechanisms has been a critical issue in providing quality-of-service (QoS) guarantees for heterogeneous traffic flows over integrated service (IntServ) and/or differentiated service (DiffServ) networks. Earliest deadline first (EDF) is an ideal scheduler for real-time services because of its optimal admissible region and delay bound properties. The major difficulty in developing an effective and efficient CAC algorithm for statistical services is the analysis of per-class deadline violation (loss) probabilities with respect to the delay bounds. In this paper, we provide an analytical approach to evaluate the aggregate and per-class deadline violation probabilities of an EDF scheduler. Based on these theoretical foundations, we derive the admission control conditions and then propose a CAC algorithm for statistic services under EDF scheduling. In addition, we show that the QoS metrics that an EDF scheduler actually guarantees have an asymptotic ordering property, which provides an important insight into the design and control of EDF networks. The effectiveness and performance of our proposed algorithm have been validated by trace-driven simulation experiments using MPEG and H.263 encoded video sources.
earliest deadline first call admission control quality-of-service deadline violation probability dominant time scale